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Overview Uplift Your Career & Skill Up to Your Dream Job - Learning Simplified From Home! Kickstart your career & boost your employability by helping you discover your skills, talents and interests with our special Microsoft Power BI Masterclass 2021 Course. You'll create a pathway to your ideal job as this course is designed to uplift your career in the relevant industry. It provides professional training that employers are looking for in today's workplaces. The Microsoft Power BI Masterclass 2021 Course is one of the most prestigious training offered at StudyHub and is highly valued by employers for good reason. This Microsoft Power BI Masterclass 2021 Course has been designed by industry experts to provide our learners with the best learning experience possible to increase their understanding of their chosen field. This Microsoft Power BI Masterclass 2021 Course, like every one of Study Hub's courses, is meticulously developed and well researched. Every one of the topics is divided into elementary modules, allowing our students to grasp each lesson quickly. At StudyHub, we don't just offer courses; we also provide a valuable teaching process. When you buy a course from StudyHub, you get unlimited Lifetime access with 24/7 dedicated tutor support. Why buy this Microsoft Power BI Masterclass 2021? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Microsoft Power BI Masterclass 2021 there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? This Microsoft Power BI Masterclass 2021 course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skill.   Prerequisites This Microsoft Power BI Masterclass 2021 does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Microsoft Power BI Masterclass 2021 was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This Microsoft Power BI Masterclass 2021 is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Section 01: Introduction Welcome! 00:01:00 What is Power BI? 00:03:00 Download & Installing Power BI Desktop 00:04:00 Getting to know the interface 00:03:00 Mini Project: Transform Data 00:07:00 Mini Project: Visualize Data 00:05:00 Mini Project: Creating a Data Model 00:07:00 Course Outline: What will you learn in this course? 00:05:00 How to learn best with this course? 00:03:00 Section 02: Preparing our Project Creating our initial project file 00:04:00 Working with the attached project files 00:04:00 Section 03: Data Transformation - The Query Editor Exploring the Query Editor 00:06:00 Connecting to our data source 00:07:00 Editing rows 00:08:00 Changing data types 00:08:00 Replacing values 00:03:00 Close & Apply 00:03:00 Connecting to a csv file 00:03:00 Connecting to a web page 00:05:00 Extracting characters 00:06:00 Splitting & merging columns 00:09:00 Creating conditional columns 00:06:00 Creating columns from examples 00:09:00 Merging Queries 00:17:00 Pivoting & Unpivoting 00:06:00 Appending Queries 00:08:00 Practice & Solution: Population table 00:15:00 The Fact-Dimension-Model 00:09:00 Practice: Load the dimension table 00:04:00 Organizing our queries in groups 00:03:00 Entering data manually 00:05:00 Creating an index column 00:03:00 Workflow & more transformations 00:05:00 Module summary 00:05:00 Exercise 1 - Instruction 00:02:00 Exercise Solution 00:11:00 Section 04: Data Transformation - Advanced Advanced Editor - Best practices 00:09:00 Performance: References vs. Duplicating 00:10:00 Performance: Enable / Disable Load & Report Refresh 00:05:00 Group by 00:05:00 Mathematical Operations 00:05:00 Run R Script 00:15:00 Using Parameters to dynamically transform data 00:06:00 M formula language: Basics 00:07:00 M formula language: Values, Lists & Tables 00:14:00 M formula language: Functions 00:13:00 M formula language: More functions & steps 00:05:00 Exercise 2 - Instructions 00:01:00 Exercise 2 - solution 00:05:00 Section 05: Creating a Data Model Understanding the relationship 00:05:00 Create & edit relationships 00:06:00 One-to-many & one-to-one relationship 00:06:00 Many-to-many (m:n) relationship 00:08:00 Cross filter direction 00:06:00 Activate & deactivate relationships 00:06:00 Model summary 00:03:00 Exercise 3 Create Model 00:02:00 Exercise 3 Solution 00:02:00 Section 06: Data Visualization Our first visual 00:08:00 The format tab 00:12:00 Understanding tables 00:10:00 Conditional formatting 00:09:00 The Pie Chart 00:06:00 All about the filter visual 00:13:00 The filter pane for developers 00:09:00 Cross filtering & edit interactions 00:04:00 Syncing slicers across pages 00:07:00 Creating drill downs 00:08:00 Creating drill throughs 00:07:00 The tree map visual 00:07:00 The decomposition tree 00:05:00 Understanding the matrix visual 00:05:00 Editing pages 00:07:00 Buttons & Actions 00:09:00 Bookmarks to customize your report 00:10:00 Analytics and Forecasts with line charts 00:10:00 Working with custom visuals 00:07:00 Get data using R Script & R Script visual 00:08:00 Asking questions - Q&A visual 00:04:00 Wrap up - data visualization 00:08:00 Section 07: Power BI & Python Python in Power BI - Plan of attack 00:03:00 Setting up Python for Power BI 00:03:00 Transforming data using Python 00:11:00 Creating visualizations using Python 00:08:00 Violin plots, pair plots & ridge plots using Python 00:15:00 Machine learning (BayesTextAnalyzer) using Python 00:00:00 Performance & Troubleshooting 00:03:00 Section 08: Storytelling with Data Introduction 00:01:00 Show Empathy & Identify the Requirement 00:03:00 Finding the Most Suitable KPI's 00:02:00 Choose an Effective Visualization 00:04:00 Make Use of Natural Reading Pattern 00:03:00 Tell a Story Using Visual Cues 00:05:00 Avoid Chaos & Group Information 00:02:00 Warp Up - Storytelling with Data 00:02:00 Section 09: DAX - The Essentials Introduction 00:03:00 The project data 00:04:00 Measures vs. Calculated Columns 00:15:00 Automatically creating a date table in DAX 00:08:00 CALENDAR 00:05:00 Creating a complete date table with features 00:04:00 Creating key measure table 00:03:00 Aggregation functions 00:06:00 The different versions of COUNT 00:14:00 SUMX - Row based calculations 00:09:00 Section 10: DAX - The CALCULATE function CALCULATE - The basics 00:11:00 Changing the context with FILTER 00:07:00 ALL 00:08:00 ALL SELECTED 00:03:00 ALL EXCEPT 00:07:00 Section 11: Power BI Service - Power BI Cloud How to go on now? 00:03:00 Power BI Pro vs Premium & Signing up 00:04:00 Exploring the interface 00:04:00 Discovering your workspace 00:03:00 Connecting Power BI Desktop & Cloud 00:04:00 Understanding datasets & reports 00:03:00 Working on reports 00:04:00 Updating reports from Power BI Desktop 00:04:00 Creating and working with workspaces 00:07:00 Installing & using a data gateway 00:13:00 Get Quick Insights 00:03:00 Creating dashboards 00:04:00 Sharing our results through Apps 00:10:00 Power BI Mobile App 00:05:00 Creating the layout for the Mobile App 00:04:00 Wrap up - Power BI Cloud 00:07:00 Section 12: Row-Level Security Introduction 00:03:00 Creating a Row-Level Security 00:05:00 Row-Level Security in the Cloud 00:04:00 Row-Level Security & Data Model 00:05:00 Dynamic Row-Level Security 00:07:00 Dynamic Many-to-Many RLS 00:04:00 Hierarchical Row-Level Security 00:13:00 Section 13: More data sources JSON & REST API 00:10:00 Setting up a local MySQL database 00:14:00 Connecting to a MySQL database in Power BI 00:05:00 Connecting to a SQL database (PostgreSQL) 00:05:00 Section 14: Next steps to improve & stay up to date Congratulations & next steps 00:06:00 The End 00:01:00 Resources Resources - Microsoft Power BI Masterclass 2021 00:00:00 Assignment Assignment - Microsoft Power BI 00:00:00

Teaching Assistants Level 1, 2 & 3 Do you aspire to be a capable teaching assistant who can meet the needs of your students? The Teaching Assistants Level 2,3 & 4 Course will help you to Discover a revolutionary curriculum to provide you with the skills and information necessary to succeed in a variety of educational environments. You will learn about the Roles and Responsibilities of the Teaching Assistant as well as various teaching environments during this Teaching Assistants Course course. You will learn how to defend supportive actions, healthy behaviours, and safety concerns in this Teaching Assistants Course. Additionally, this Teaching Assistants Course will help you strengthen your mentoring, organising, and understanding of children's growth. You may encourage equality, diversity, and inclusion in work with the aid of this Teaching Assistants Course. Enrol in the Teaching Assistants Course to develop your ability to work with a range of students! Special Offers of this Teaching Assistants Level 1, 2 & 3 Course This Teaching Assistants Course includes a FREE PDF Certificate. Lifetime Access to this Teaching Assistants Course Instant Access to this Teaching Assistants Course Get FREE Tutor Support to this Teaching Assistants Course Teaching Assistants Level 1, 2 & 3 You will also learn about a variety of Teaching Assistants Level 1, 2 & 3 concepts and approaches that have impacted contemporary primary teaching support practices in this Teaching Assistants Level 1,2 & 3 course. So, start your journey to a fulfilling career in education by enrolling in our Teaching Assistants Level 1, 2 & 3 course right now! [ Special Note: This Teaching Assistants Level 1, 2 & 3 Courses are CPD Accredited knowledge based Course & we don't offer any formal Qualification ] Who is this course for? Teaching Assistants Level 1, 2 & 3 For those who desire to work as teaching assistants and obtain a recognised qualification in this profession, this Teaching Assistants Level 1, 2 & 3 course has been created. This Teaching Assistants Level 1, 2 & 3 course will help you to go advance level in the field of Teaching Assistant. You can enrol on higher level Teaching Assistant courses, such as: Level 2 Award in Teaching Assistant Practice Level 2 Certificate in Teaching Assistant Practice Level 3 Certificate in Teaching Assistant Studies Level 3 Diploma in Teaching Assistant Studies Level 4 Certificate in Teaching Assistant Leadership Level 4 Diploma in Teaching Assistant Leadership Level 5 Diploma in Teaching Assistant Management Level 6 Diploma in Teaching Assistant Research Level 4 Certificate in Higher Level Teaching Assistant (HLTA) Level 5 Higher Level Teaching Assistant (HLTA) Requirements Teaching Assistants Level 1, 2 & 3 To enrol in this Teaching Assistants Level 1, 2 & 3 Course, students must fulfil the following requirements. To join in our Teaching Assistant Course, you must have a strong command of the English language. To successfully complete our Teaching Assistant Course, you must be vivacious and self driven. To complete our Teaching Assistant Course, you must have a basic understanding of computers. Career path Teaching Assistants Level 1, 2 & 3 This credential in Teaching Assistants Level 1, 2 & 3 courses will open up several paths including: Higher Level Teaching Assistant Primary Teaching Assistant Montessori Educator

Dive into the enthralling world of numbers and equations with 'High School Math (Pure Mathematics 1),' a course designed to unravel the mysteries of mathematics. Your journey begins with an Introduction that lays the foundation, not just in terms of concepts but igniting a passion for the beauty of math. As you progress, Functions become more than just equations; they turn into a language that describes the universe. Imagine the elegance of Quadratic Equations unfolding before your eyes, revealing patterns and solutions that were once hidden. Embark on an adventure through Co-ordinate Geometry, where every point and line tells a story of space and dimensions. Sequence and Series will no longer be just about numbers; they will be about the rhythm and flow of mathematical logic. The course takes a deeper dive with the Binomial Theorem, Differentiation, Tangents and Normals, each module building on the last, turning complexity into simplicity. Stationary Points & Curve Sketching, and the Second Derivative Test open new vistas in understanding the nature of graphs. As you master Simultaneous Linear Equations, you're not just solving problems; you're unlocking a new perspective on mathematical relationships. The Essential Revision at the end is your bridge to excellence, consolidating your knowledge and skills. Learning Outcomes Develop a foundational understanding of key mathematical concepts and functions. Master the intricacies of quadratic equations and co-ordinate geometry. Explore and apply the principles of sequences, series, and the binomial theorem. Gain proficiency in differentiation and its practical applications in tangents and normals. Understand and implement techniques in curve sketching, stationary points, and optimisation. Why choose this High School Math (Pure Mathematics 1) course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this High School Math (Pure Mathematics 1) course for? High school students seeking to excel in mathematics. Individuals preparing for college-level math courses. Math enthusiasts looking to deepen their understanding of pure mathematics. Students requiring a comprehensive revision of key mathematical concepts. Anyone aspiring to pursue a career involving advanced mathematics. Career path Mathematician: £30,000 - £60,000 Data Analyst: £25,000 - £50,000 Actuarial Analyst: £28,000 - £55,000 Research Scientist (Mathematics): £32,000 - £60,000 Engineering Consultant: £27,000 - £55,000 Academic Tutor (Mathematics): £24,000 - £40,000 Prerequisites This High School Math (Pure Mathematics 1) does not require you to have any prior qualifications or experience. You can just enrol and start learning.This High School Math (Pure Mathematics 1) was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Introduction Introduction 00:03:00 Functions What is Function? 00:07:00 Vertical Line Test 00:04:00 Value of a Function Graphically 00:08:00 Domain Range of a function Algebraically 00:13:00 Domain Range of a function Graphically 00:06:00 Even & Odd Functions 00:07:00 One to one Function 00:05:00 Composite Functions 00:09:00 How to draw Rational Functions- 1 00:04:00 How to draw Rational Functions- 2 00:10:00 Inverse of a function Algebraically 00:05:00 Inverse of a function Graphically 00:09:00 Practice Problems 00:15:00 Practice Problems 00:11:00 Resources Downloads 00:40:00 Quadratic Equations Introduction to Quadratic Equations 00:04:00 Solving Quadratic Equations by Factorization method 00:10:00 Writing in completed square form 00:08:00 Solving by completed square method 00:08:00 Sketching of Quadratic Graphs 00:11:00 Quadratic graphs using Transformations 00:06:00 Quadratic inequalities 00:11:00 Deriving Quadratic formula 00:05:00 Solving problems using Quadratic Formula 00:06:00 Equations reducible to Quadratic 00:07:00 Nature of Roots of Quadratic Equations 00:04:00 Nature of roots continues 00:12:00 Quadratic Equations (Resources) 00:50:00 Co-ordinate Geometry Distance formula 00:15:00 Mid point formula 00:05:00 Gradient of a line 00:10:00 Graphing using gradient and y intercept 00:02:00 Some standard lines 00:04:00 Slope intercept form y = m x +c 00:05:00 Point slope form and two point form 00:10:00 Intersection of line and parabola 00:09:00 Practice Problems from past papers (part 3) 00:12:00 Sequence and series Sequence and series ( video) 00:08:00 Arithmetic Sequence 00:10:00 General term of an A.P. 00:07:00 Finding given term is which term? 00:05:00 Writing sequence when two terms are known 00:08:00 Condition for three terms to be in A.P. 00:05:00 Sum to n terms of A.P. 00:06:00 Practice Problems 1 (A.P.) 00:08:00 Practice problems 3 (A.P.) 00:07:00 Practice problems 4 (A.P.) 00:10:00 Geometric Progressions 00:11:00 Sum to n terms in G.P. 00:14:00 Sum to infinite Terms in G.P. 00:13:00 Practice Problems 1 (GP) 00:13:00 Practice Problems 2 (GP) 00:06:00 Practice Problems based on AP and GP both 00:15:00 Sequence and series Text 1 00:40:00 Sequence and series Text 2 00:55:00 Binomial Theorem What is Factorial? 00:06:00 n-choose -r problems 00:06:00 Properties of n - choose -r 00:05:00 Expanding using Binomial Theorem 00:11:00 Finding the indicated term in the Binomial expansion 00:10:00 Finding the indicated term from end 00:09:00 Finding the coefficient for given exponent (index) of the variable 00:08:00 Finding the term independent of variable 00:05:00 Expanding in increasing and decreasing powers of x 00:09:00 Practice problems 1 00:12:00 Practice Problems 2 00:09:00 Practice problems 3 00:10:00 Past papers problems 1 00:15:00 Past Paper problems 2 00:13:00 Past Paper problems 3 00:09:00 Resources in this section 00:50:00 Differentiation What is Derivative? 00:07:00 Derivation of formula for Derivative 00:06:00 Differentiation by definition or First Principle 00:06:00 Power Rule 00:20:00 Practice Problems on Power Rule 1 00:07:00 Practice Problems on Power Rule 2 00:07:00 Practice Problems on Power Rule 3 00:05:00 Practice Problems on Power Rule 4 00:11:00 Practice Problems on Power Rule 5 00:07:00 Tangents and Normals Tangents and Normals- Basics 00:12:00 Practice- Tangents and Normals Part 1 00:16:00 Practice- Tangents and Normals Part 2 00:13:00 Practice- Tangents and Normals Part 3 00:11:00 Practice- Tangents and Normals Part 4 00:14:00 Stationary Points & Curve Sketching Stationary Points - Basics 00:13:00 Practice- Increasing Decreasing & Maxima Minima part 1 00:11:00 Practice- Increasing Decreasing & Maxima Minima part 2 00:12:00 Practice- Increasing Decreasing & Maxima Minima part 3 00:10:00 Second Derivative Test (Maximum & Minimum Points) Concavity-Basics 00:02:00 Concavity & Second Derivative 00:08:00 Second Derivative Test 00:09:00 Practice Problems on second derivative 00:04:00 Practice Problem of Maxima Minima using second derivative test Part 1 00:17:00 Practice Problem of Maxima Minima using second derivative test Part 2 00:10:00 Practice Problem of Maxima Minima using second derivative test Part 3 00:07:00 Practice Problem of Maxima Minima using second derivative test Part 4 00:07:00 Applications of Maxima and Minima Part 1 00:09:00 Applications of Maxima and Minima Part 2 00:07:00 Applications of Maxima and Minima Part 3 00:10:00 Applications of Maxima and Minima Part 4 00:09:00 Applications of Maxima and Minima Part 5 00:10:00 Applications of Maxima and Minima Part 6 00:08:00 Past Paper Problems on applications of maxima and minima Part 1 00:09:00 Past Paper Problems on applications of maxima and minima Part 2 00:09:00 Past Paper Problems on applications of maxima and minima Part 3 00:08:00 Past Paper Problems on applications of maxima and minima Part 4 00:07:00 Chain Rule 00:12:00 Rate of change part 1 00:05:00 Rate of change part 2 00:10:00 Rate of change part 3 00:07:00 Past Paper Problems using chain rule -1 00:06:00 Past Paper Problems using chain rule - 2 00:07:00 Past Paper Problems using chain rule 3 00:07:00 Past Paper Problems using chain rule -4 00:04:00 Simultaneous Linear equations Graphical Method of solving pair of linear equations 00:10:00 Video lecture on Graphical method 00:05:00 Method of elimination by substitution 00:10:00 Video lecture on substitution method 00:06:00 Method of elimination by equating the coefficients 00:10:00 Video lecture on equating coefficients method 00:09:00 Practice Problems on Linear equation 00:20:00 Essential Revision How to take up this course? 00:10:00 Background of Algebra 00:10:00 Language of Alg ebra 00:10:00 Finding Values of algebraic expressions 00:14:00 Fractional Indices 00:10:00 Higher Indices 00:07:00 Rules of Brackets 00:04:00 Simplification by removing brackets (BODMAS) 00:11:00 Simplifications of Algebraic Fractions 00:07:00 Solving complex Linear Equations in one variable 00:10:00 Factorization by taking out common factor 00:10:00 Factorization by grouping the terms 00:09:00 Factorize using identity a ² - b ² 00:07:00 Factorization by middle term split 00:12:00

Are you embarking on the journey of mastering data analytics and visualisation in the UK? The 'Advanced Diploma in Microsoft Power BI 2021 at QLS Level 7' is your beacon. Positioned to illuminate the intricate realm of Power BI, this course offers a comprehensive look into the foundational aspects and the advanced features that make Microsoft's tool a standout. With sections meticulously designed ranging from the fundamentals, like data transformation, to advanced concepts, such as integrating Power BI with Python and storytelling with data, this course ensures learners grasp the complete spectrum. With the rising emphasis on data analytics in today's business world, this course acquaints you with Power BI's prowess. It prepares you for the sought-after Microsoft Power BI certification in the UK. Learning Outcomes Comprehend the fundamental aspects of Power BI, from initiating a project to understanding the user interface. Develop proficiency in advanced data transformation techniques and data model creation. Integrate Python with Power BI and harness the benefits of both for enhanced data analytics. Master the art of 'Storytelling with Data' to deliver impactful presentations and reports. Understand and implement Row-Level Security and harness Power BI Cloud services efficiently. Why choose this Advanced Diploma in Microsoft Power BI 2021 at QLS Level 7? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments are designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Who is this Advanced Diploma in Microsoft Power BI 2021 at QLS Level 7 for? Individuals keen on obtaining the Microsoft power bi certification UK. Analysts and data professionals aspiring to enhance their data visualisation skills. Business professionals wanting to leverage Power BI for insightful business decision-making. Tech enthusiasts aiming to amalgamate programming (Python) with data analytics. Those seeking to stay updated with the latest trends in Power BI and its evolving capabilities. Career path Data Analyst: Average Salary £30,000 - £40,000 Annually Business Intelligence Developer: Average Salary £35,000 - £45,000 Annually Power BI Developer: Average Salary £40,000 - £50,000 Annually Data Visualisation Specialist: Average Salary £32,000 - £42,000 Annually Business Intelligence Manager: Average Salary £45,000 - £55,000 Annually Data Strategy Consultant: Average Salary £50,000 - £60,000 Annually Prerequisites This Advanced Diploma in Microsoft Power BI 2021 at QLS Level 7 does not require you to have any prior qualifications or experience. You can just enrol and start learning. This course was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Endorsed Certificate of Achievement from the Quality Licence Scheme Learners will be able to achieve an endorsed certificate after completing the course as proof of their achievement. You can order the endorsed certificate for only £135 to be delivered to your home by post. For international students, there is an additional postage charge of £10. Endorsement The Quality Licence Scheme (QLS) has endorsed this course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the course has been reviewed and approved by the QLS and meets the highest quality standards. Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. Course Curriculum Section 01: Introduction Welcome! 00:01:00 What is Power BI? 00:03:00 Download & Installing Power BI Desktop 00:04:00 Getting to know the interface 00:03:00 Mini Project: Transform Data 00:07:00 Mini Project: Visualize Data 00:05:00 Mini Project: Creating a Data Model 00:07:00 Course Outline: What will you learn in this course? 00:05:00 How to learn best with this course? 00:03:00 Section 02: Preparing our Project Creating our initial project file 00:04:00 Working with the attached project files 00:04:00 Section 03: Data Transformation - The Query Editor Exploring the Query Editor 00:06:00 Connecting to our data source 00:07:00 Editing rows 00:08:00 Changing data types 00:08:00 Replacing values 00:03:00 Close & Apply 00:03:00 Connecting to a csv file 00:03:00 Connecting to a web page 00:05:00 Extracting characters 00:06:00 Splitting & merging columns 00:09:00 Creating conditional columns 00:06:00 Creating columns from examples 00:09:00 Merging Queries 00:17:00 Pivoting & Unpivoting 00:06:00 Appending Queries 00:08:00 Practice & Solution: Population table 00:15:00 The Fact-Dimension-Model 00:09:00 Practice: Load the dimension table 00:04:00 Organizing our queries in groups 00:03:00 Entering data manually 00:05:00 Creating an index column 00:03:00 Workflow & more transformations 00:05:00 Module summary 00:05:00 Exercise 1 - Instruction 00:02:00 Exercise Solution 00:11:00 Section 04: Data Transformation - Advanced Advanced Editor - Best practices 00:09:00 Performance: References vs. Duplicating 00:10:00 Performance: Enable / Disable Load & Report Refresh 00:05:00 Group by 00:05:00 Mathematical Operations 00:05:00 Run R Script 00:15:00 Using Parameters to dynamically transform data 00:06:00 M formula language: Basics 00:07:00 M formula language: Values, Lists & Tables 00:14:00 M formula language: Functions 00:13:00 M formula language: More functions & steps 00:05:00 Exercise 2 - Instructions 00:01:00 Exercise 2 - solution 00:05:00 Section 05: Creating a Data Model Understanding the relationship 00:05:00 Create & edit relationships 00:06:00 One-to-many & one-to-one relationship 00:06:00 Many-to-many (m:n) relationship 00:08:00 Cross filter direction 00:06:00 Activate & deactivate relationships 00:06:00 Model summary 00:03:00 Exercise 3 Create Model 00:03:00 Exercise 3 Solution 00:02:00 Section 06: Data Visualization Our first visual 00:08:00 The format tab 00:12:00 Understanding tables 00:10:00 Conditional formatting 00:09:00 The Pie Chart 00:06:00 All about the filter visual 00:13:00 The filter pane for developers 00:09:00 Cross filtering & edit interactions 00:04:00 Syncing slicers across pages 00:07:00 Creating drill downs 00:08:00 Creating drill throughs 00:07:00 The tree map visual 00:07:00 The decomposition tree 00:05:00 Understanding the matrix visual 00:05:00 Editing pages 00:07:00 Buttons & Actions 00:09:00 Bookmarks to customize your report 00:10:00 Analytics and Forecasts with line charts 00:10:00 Working with custom visuals 00:07:00 Get data using R Script & R Script visual 00:08:00 Asking questions - Q&A visual 00:04:00 Wrap up - data visualization 00:08:00 Section 07: Power BI & Python Python in Power BI - Plan of attack 00:03:00 Setting up Python for Power BI 00:03:00 Transforming data using Python 00:11:00 Creating visualizations using Python 00:08:00 Violin plots, pair plots & ridge plots using Python 00:15:00 Machine learning (BayesTextAnalyzer) using Python 00:00:00 Performance & Troubleshooting 00:03:00 Section 08: Storytelling with Data Introduction 00:01:00 Show Empathy & Identify the Requirement 00:03:00 Finding the Most Suitable KPI's 00:02:00 Choose an Effective Visualization 00:04:00 Make Use of Natural Reading Pattern 00:03:00 Tell a Story Using Visual Cues 00:05:00 Avoid Chaos & Group Information 00:02:00 Warp Up - Storytelling with Data 00:02:00 Section 09: DAX - The Essentials Introduction 00:03:00 The project data 00:04:00 Measures vs. Calculated Columns 00:15:00 Automatically creating a date table in DAX 00:08:00 CALENDAR 00:05:00 Creating a complete date table with features 00:04:00 Creating key measure table 00:03:00 Aggregation functions 00:06:00 The different versions of COUNT 00:14:00 SUMX - Row based calculations 00:09:00 Section 10: DAX - The CALCULATE function CALCULATE - The basics 00:11:00 Changing the context with FILTER 00:07:00 ALL 00:08:00 ALL SELECTED 00:03:00 ALL EXCEPT 00:07:00 Section 11: Power BI Service - Power BI Cloud How to go on now? 00:03:00 Power BI Pro vs Premium & Signing up 00:04:00 Exploring the interface 00:04:00 Discovering your workspace 00:03:00 Connecting Power BI Desktop & Cloud 00:04:00 Understanding datasets & reports 00:03:00 Working on reports 00:04:00 Updating reports from Power BI Desktop 00:04:00 Creating and working with workspaces 00:07:00 Installing & using a data gateway 00:13:00 Get Quick Insights 00:03:00 Creating dashboards 00:04:00 Sharing our results through Apps 00:10:00 Power BI Mobile App 00:05:00 Creating the layout for the Mobile App 00:04:00 Wrap up Power BI Cloud 00:07:00 Section 12: Row-Level Security Introduction 00:03:00 Creating a Row-Level Security 00:05:00 Row-Level Security in the Cloud 00:04:00 Row-Level Security & Data Model 00:05:00 Dynamic Row-Level Security 00:07:00 Dynamic Many-to-Many RLS 00:04:00 Hierarchical Row-Level Security 00:13:00 Section 13: More data sources JSON & REST API 00:10:00 Setting up a local MySQL database 00:14:00 Connecting to a MySQL database in Power BI 00:05:00 Connecting to a SQL database (PostgreSQL) 00:05:00 Section 14: Next steps to improve & stay up to date Congratulations & next steps 00:06:00 The End 00:01:00 Resources Resources - Advanced Diploma in Microsoft Power BI 2021 at QLS Level 7 00:00:00 Assignment Assignment - Advanced Diploma in Microsoft Power BI 2021 at QLS Level 7 04:00:00 Order your QLS Endorsed Certificate Order your QLS Endorsed Certificate 00:00:00

Overview Construction management is vast, and the global construction market is forecasted to grow by 85% to $15.5 TRILLION worldwide by 2030. The Diploma in Construction Management becomes an essential learning tool for those aspiring to spearhead this growth. This comprehensive course covers all the critical facts of construction management, equipping students with the essential knowledge and in-demand skills to oversee complex Construction projects seamlessly. This Construction diploma covers everything from the project life cycle to the legal aspects of contracting, giving you a complete understanding of construction management. Key Features of the Course: FREE Construction Management CPD-accredited certificate Get a free student ID card with Construction Management training (£10 applicable for international delivery) Lifetime access to the Construction Management course materials The Construction Management program comes with 24/7 tutor support Get instant access to this Construction Management course Learn Construction Management training from anywhere in the world The Construction Management training is affordable and simple to understand The Construction Management training is an entirely online Description This course provides essential knowledge and skills for managing construction projects effectively. Learn about project planning, budgeting, team coordination, and legal requirements to confidently oversee construction projects from start to finish. Course Curriculum: 1 sections • 18 lectures • 06:43:00 hours total •Module 01: Introduction to Construction Management •Module 02: Project Life Cycle and Success •Module 03: Cost Management •Module 04: Preliminary Site Investigation and Site Organization •Module 05: Site Management •Module 06: Planning and Management of Equipment •Module 07: Construction Materials Management •Module 08: Vendor Analysis in Construction Management •Module 09: Construction Procurement •Module 10: Stock Control •Module 11: Supply Chain Management •Module 12: The Main Participators •Module 13: Quality Assurance and Customer Care •Module 14: Legal Aspects of Contracting •Module 15: Human Resources Management •Module 16: Risk and Value Management •Module 17: Communications, Information and Documentation of Construction •Module 18: Health and Safety in Construction Management Career path Having these various qualifications will increase the value of your CV and open you up to multiple sectors such as: Construction Manager Site Manager Project Manager Quantity Surveyor Estimator Site Engineer Building Surveyor Health and Safety Manager Sustainability Manager General Foreman

The 'Complete Python Machine Learning & Data Science Fundamentals' course covers the foundational concepts of machine learning, data science, and Python programming. It includes hands-on exercises, data visualization, algorithm evaluation techniques, feature selection, and performance improvement using ensembles and parameter tuning. Learning Outcomes: Understand the fundamental concepts and types of machine learning, data science, and Python programming. Learn to prepare the system and environment for data analysis and machine learning tasks. Master the basics of Python, NumPy, Matplotlib, and Pandas for data manipulation and visualization. Gain insights into dataset summary statistics, data visualization techniques, and data preprocessing. Explore feature selection methods and evaluation metrics for classification and regression algorithms. Compare and select the best machine learning model using pipelines and ensembles. Learn to export, save, load machine learning models, and finalize the chosen models for real-time predictions. Why buy this Complete Python Machine Learning & Data Science Fundamentals? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Complete Python Machine Learning & Data Science Fundamentals there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? This Complete Python Machine Learning & Data Science Fundamentals course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skill. Prerequisites This Complete Python Machine Learning & Data Science Fundamentals does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Complete Python Machine Learning & Data Science Fundamentals was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This Complete Python Machine Learning & Data Science Fundamentals is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Course Overview & Table of Contents Course Overview & Table of Contents 00:09:00 Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types 00:05:00 Introduction to Machine Learning - Part 2 - Classifications and Applications Introduction to Machine Learning - Part 2 - Classifications and Applications 00:06:00 System and Environment preparation - Part 1 System and Environment preparation - Part 1 00:08:00 System and Environment preparation - Part 2 System and Environment preparation - Part 2 00:06:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 1 00:10:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 2 00:09:00 Learn Basics of python - Functions Learn Basics of python - Functions 00:04:00 Learn Basics of python - Data Structures Learn Basics of python - Data Structures 00:12:00 Learn Basics of NumPy - NumPy Array Learn Basics of NumPy - NumPy Array 00:06:00 Learn Basics of NumPy - NumPy Data Learn Basics of NumPy - NumPy Data 00:08:00 Learn Basics of NumPy - NumPy Arithmetic Learn Basics of NumPy - NumPy Arithmetic 00:04:00 Learn Basics of Matplotlib Learn Basics of Matplotlib 00:07:00 Learn Basics of Pandas - Part 1 Learn Basics of Pandas - Part 1 00:06:00 Learn Basics of Pandas - Part 2 Learn Basics of Pandas - Part 2 00:07:00 Understanding the CSV data file Understanding the CSV data file 00:09:00 Load and Read CSV data file using Python Standard Library Understanding the CSV data file 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using Python Standard Library 00:09:00 Load and Read CSV data file using Pandas Load and Read CSV data file using Pandas 00:05:00 Dataset Summary - Peek, Dimensions and Data Types Dataset Summary - Peek, Dimensions and Data Types 00:09:00 Dataset Summary - Class Distribution and Data Summary Dataset Summary - Class Distribution and Data Summary 00:09:00 Dataset Summary - Explaining Correlation Dataset Summary - Explaining Correlation 00:11:00 Dataset Summary - Explaining Skewness - Gaussian and Normal Curve Dataset Summary - Explaining Skewness - Gaussian and Normal Curve 00:07:00 Dataset Visualization - Using Histograms Dataset Visualization - Using Histograms 00:07:00 Dataset Visualization - Using Density Plots Dataset Visualization - Using Density Plots 00:06:00 Dataset Visualization - Box and Whisker Plots Dataset Visualization - Box and Whisker Plots 00:05:00 Multivariate Dataset Visualization - Correlation Plots Multivariate Dataset Visualization - Correlation Plots 00:08:00 Multivariate Dataset Visualization - Scatter Plots Multivariate Dataset Visualization - Scatter Plots 00:05:00 Data Preparation (Pre-Processing) - Introduction Data Preparation (Pre-Processing) - Introduction 00:09:00 Data Preparation - Re-scaling Data - Part 1 Data Preparation - Re-scaling Data - Part 1 00:09:00 Data Preparation - Re-scaling Data - Part 2 Data Preparation - Re-scaling Data - Part 2 00:09:00 Data Preparation - Standardizing Data - Part 1 Data Preparation - Standardizing Data - Part 1 00:07:00 Data Preparation - Standardizing Data - Part 2 Data Preparation - Standardizing Data - Part 2 00:04:00 Data Preparation - Normalizing Data Data Preparation - Normalizing Data 00:08:00 Data Preparation - Binarizing Data Data Preparation - Binarizing Data 00:06:00 Feature Selection - Introduction Feature Selection - Introduction 00:07:00 Feature Selection - Uni-variate Part 1 - Chi-Squared Test Feature Selection - Uni-variate Part 1 - Chi-Squared Test 00:09:00 Feature Selection - Uni-variate Part 2 - Chi-Squared Test Feature Selection - Uni-variate Part 2 - Chi-Squared Test 00:10:00 Feature Selection - Recursive Feature Elimination Feature Selection - Recursive Feature Elimination 00:11:00 Feature Selection - Principal Component Analysis (PCA) Feature Selection - Principal Component Analysis (PCA) 00:09:00 Feature Selection - Feature Importance Feature Selection - Feature Importance 00:07:00 Refresher Session - The Mechanism of Re-sampling, Training and Testing Refresher Session - The Mechanism of Re-sampling, Training and Testing 00:12:00 Algorithm Evaluation Techniques - Introduction Algorithm Evaluation Techniques - Introduction 00:07:00 Algorithm Evaluation Techniques - Train and Test Set Algorithm Evaluation Techniques - Train and Test Set 00:11:00 Algorithm Evaluation Techniques - K-Fold Cross Validation Algorithm Evaluation Techniques - K-Fold Cross Validation 00:09:00 Algorithm Evaluation Techniques - Leave One Out Cross Validation Algorithm Evaluation Techniques - Leave One Out Cross Validation 00:05:00 Algorithm Evaluation Techniques - Repeated Random Test-Train Splits Algorithm Evaluation Techniques - Repeated Random Test-Train Splits 00:07:00 Algorithm Evaluation Metrics - Introduction Algorithm Evaluation Metrics - Introduction 00:09:00 Algorithm Evaluation Metrics - Classification Accuracy Algorithm Evaluation Metrics - Classification Accuracy 00:08:00 Algorithm Evaluation Metrics - Log Loss Algorithm Evaluation Metrics - Log Loss 00:03:00 Algorithm Evaluation Metrics - Area Under ROC Curve Algorithm Evaluation Metrics - Area Under ROC Curve 00:06:00 Algorithm Evaluation Metrics - Confusion Matrix Algorithm Evaluation Metrics - Confusion Matrix 00:10:00 Algorithm Evaluation Metrics - Classification Report Algorithm Evaluation Metrics - Classification Report 00:04:00 Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction 00:06:00 Algorithm Evaluation Metrics - Mean Absolute Error Algorithm Evaluation Metrics - Mean Absolute Error 00:07:00 Algorithm Evaluation Metrics - Mean Square Error Algorithm Evaluation Metrics - Mean Square Error 00:03:00 Algorithm Evaluation Metrics - R Squared Algorithm Evaluation Metrics - R Squared 00:04:00 Classification Algorithm Spot Check - Logistic Regression Classification Algorithm Spot Check - Logistic Regression 00:12:00 Classification Algorithm Spot Check - Linear Discriminant Analysis Classification Algorithm Spot Check - Linear Discriminant Analysis 00:04:00 Classification Algorithm Spot Check - K-Nearest Neighbors Classification Algorithm Spot Check - K-Nearest Neighbors 00:05:00 Classification Algorithm Spot Check - Naive Bayes Classification Algorithm Spot Check - Naive Bayes 00:04:00 Classification Algorithm Spot Check - CART Classification Algorithm Spot Check - CART 00:04:00 Classification Algorithm Spot Check - Support Vector Machines Classification Algorithm Spot Check - Support Vector Machines 00:05:00 Regression Algorithm Spot Check - Linear Regression Regression Algorithm Spot Check - Linear Regression 00:08:00 Regression Algorithm Spot Check - Ridge Regression Regression Algorithm Spot Check - Ridge Regression 00:03:00 Regression Algorithm Spot Check - Lasso Linear Regression Regression Algorithm Spot Check - Lasso Linear Regression 00:03:00 Regression Algorithm Spot Check - Elastic Net Regression Regression Algorithm Spot Check - Elastic Net Regression 00:02:00 Regression Algorithm Spot Check - K-Nearest Neighbors Regression Algorithm Spot Check - K-Nearest Neighbors 00:06:00 Regression Algorithm Spot Check - CART Regression Algorithm Spot Check - CART 00:04:00 Regression Algorithm Spot Check - Support Vector Machines (SVM) Regression Algorithm Spot Check - Support Vector Machines (SVM) 00:04:00 Compare Algorithms - Part 1 : Choosing the best Machine Learning Model Compare Algorithms - Part 1 : Choosing the best Machine Learning Model 00:09:00 Compare Algorithms - Part 2 : Choosing the best Machine Learning Model Compare Algorithms - Part 2 : Choosing the best Machine Learning Model 00:05:00 Pipelines : Data Preparation and Data Modelling Pipelines : Data Preparation and Data Modelling 00:11:00 Pipelines : Feature Selection and Data Modelling Pipelines : Feature Selection and Data Modelling 00:10:00 Performance Improvement: Ensembles - Voting Performance Improvement: Ensembles - Voting 00:07:00 Performance Improvement: Ensembles - Bagging Performance Improvement: Ensembles - Bagging 00:08:00 Performance Improvement: Ensembles - Boosting Performance Improvement: Ensembles - Boosting 00:05:00 Performance Improvement: Parameter Tuning using Grid Search Performance Improvement: Parameter Tuning using Grid Search 00:08:00 Performance Improvement: Parameter Tuning using Random Search Performance Improvement: Parameter Tuning using Random Search 00:06:00 Export, Save and Load Machine Learning Models : Pickle Export, Save and Load Machine Learning Models : Pickle 00:10:00 Export, Save and Load Machine Learning Models : Joblib Export, Save and Load Machine Learning Models : Joblib 00:06:00 Finalizing a Model - Introduction and Steps Finalizing a Model - Introduction and Steps 00:07:00 Finalizing a Classification Model - The Pima Indian Diabetes Dataset Finalizing a Classification Model - The Pima Indian Diabetes Dataset 00:07:00 Quick Session: Imbalanced Data Set - Issue Overview and Steps Quick Session: Imbalanced Data Set - Issue Overview and Steps 00:09:00 Iris Dataset : Finalizing Multi-Class Dataset Iris Dataset : Finalizing Multi-Class Dataset 00:09:00 Finalizing a Regression Model - The Boston Housing Price Dataset Finalizing a Regression Model - The Boston Housing Price Dataset 00:08:00 Real-time Predictions: Using the Pima Indian Diabetes Classification Model Real-time Predictions: Using the Pima Indian Diabetes Classification Model 00:07:00 Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset 00:03:00 Real-time Predictions: Using the Boston Housing Regression Model Real-time Predictions: Using the Boston Housing Regression Model 00:08:00 Resources Resources - Python Machine Learning & Data Science Fundamentals 00:00:00

Embark on a transformative journey through the intricate landscape of networking with the CompTIA Network+ Certification (N10-007). This course isn't just about mastering the intricacies of network models or delving into the depths of cabling and topology; it's about empowering yourself with the skills and knowledge to navigate the digital highways of the modern era confidently. Picture yourself as the architect, laying down the foundations of robust networks, securing them against digital threats, and troubleshooting with finesse. With CompTIA Network+ +, you're not just learning; you're shaping your future in information technology. In this comprehensive course, you'll traverse through 22 meticulously crafted sections, each unlocking a new facet of comptia networking. From understanding the fundamentals of TCP/IP to exploring the nuances of wireless networking and delving into virtualization and cloud computing, every lesson is a stepping stone towards network mastery. Through immersive learning experiences and hands-on comptia network+ practice tests, you'll absorb theoretical knowledge and hone your practical skills, preparing you for real-world challenges. Learning Outcomes: Master network models and topologies, laying a strong foundation for network architecture. Demonstrate proficiency in TCP/IP fundamentals and routing protocols for effective data transmission. Develop expertise in securing networks against cyber threats, ensuring data integrity and confidentiality. Acquire skills in network troubleshooting and monitoring, enabling swift resolution of issues. Apply wireless networking and cloud computing knowledge to design and implement scalable network solutions. Why buy this CompTIA Network+ Certification (N10-007)? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the CompTIA Network+ Certification (N10-007) there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this CompTIA Network+ Certification (N10-007) for? Aspiring IT professionals seeking to kickstart their careers in networking. Students aiming to enhance their employability with industry-recognized certifications. Career changers looking to transition into the dynamic field of information technology. IT professionals seeking to validate their skills and advance their careers. Anyone passionate about mastering the intricacies of comptia network and carving a niche in the digital landscape. Prerequisites This CompTIA Network+ Certification (N10-007) does not require you to have any prior qualifications or experience. You can just enrol and start learning.This CompTIA Network+ Certification (N10-007) was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path Network Administrator: £20,000 - £45,000 Per Annum Network Engineer: £25,000 - £55,000 Per Annum Systems Administrator: £22,000 - £50,000 Per Annum IT Support Technician: £18,000 - £35,000 Per Annum Cyber Security Analyst: £25,000 - £60,000 Per Annum Cloud Solutions Architect: £30,000 - £80,000 Per Annum Course Curriculum Section 01: Introduction Introduction 00:03:00 Section 02: Network Models What is a Model? 00:02:00 OSI vs. TCP/IP Model 00:07:00 Walking Through OSI and TCP/IP 00:12:00 Meet the Frame 00:06:00 The MAC Address 00:07:00 Broadcast vs. Unicast 00:04:00 Introduction to IP Addressing 00:08:00 Packets and Ports 00:05:00 Section 03: Cabling and Topology Network Topologies 00:10:00 Coaxial Cabling 00:05:00 Twisted Pair Cabling 00:06:00 Cat Ratings 00:06:00 Fiber Optic Cabling 00:09:00 Fire Ratings 00:05:00 Legacy Network Connections 00:07:00 Section 04: Ethernet Basics What is Ethernet? 00:07:00 Ethernet Frames 00:07:00 Early Ethernet 00:08:00 The Daddy of Ethernet, 10BaseT 00:03:00 Terminating Twisted Pair 00:14:00 Hubs vs. Switches 00:13:00 Section 05: Modern Ethernet 100BaseT 00:05:00 Connecting Switches 00:05:00 Gigabit Ethernet and 10-Gigabit Ethernet 00:05:00 Transceivers 00:07:00 Connecting Ethernet Scenarios 00:14:00 Section 06: Installing a Physical Network Introduction to Structured Cabling 00:04:00 Terminating Structured Cabling 00:08:00 Equipment Room 00:07:00 Alternative Distribution Panels 00:04:00 Testing Cable 00:09:00 Troubleshooting Structured Cabling, Part 1 00:05:00 Troubleshooting Structured Cabling, Part 2 00:05:00 Using a Toner and Probe 00:03:00 Wired Connection Scenarios 00:11:00 Section 07: TCP/IP Basics Introduction to IP Addressing and Binary 00:13:00 Introduction to ARP 00:04:00 Classful Addressing 00:10:00 Subnet Masks 00:12:00 Subnetting with CIDR 00:10:00 More CIDR Subnetting Practice 00:10:00 Dynamic and Static IP Addressing 00:18:00 Rogue DHCP Servers 00:07:00 Special IP Addresses 00:07:00 IP Addressing Scenarios 00:15:00 Section 08: Routing Introducing Routers 00:15:00 Understanding Ports 00:05:00 Network Address Translation 00:06:00 Implementing NAT 00:03:00 Forwarding Ports 00:18:00 Tour of a SOHO Router 00:12:00 SOHO vs. Enterprise 00:09:00 Static Routes 00:13:00 Dynamic Routing 00:11:00 RIP 00:04:00 OSPF 00:04:00 BGP 00:06:00 Section 09: TCP/IP Applications TCP and UDP 00:07:00 ICMP and IGMP 00:06:00 Handy Tools 00:07:00 Introduction to Wireshark 00:11:00 Introduction to netstat 00:09:00 Web Servers 00:12:00 FTP 00:12:00 E-mail Servers and Clients 00:09:00 Securing E-mail 00:06:00 Telnet and SSH 00:09:00 Network Time Protocol 00:02:00 Network Service Scenarios 00:10:00 Section 10: Network Naming Understanding DNS 00:12:00 Applying DNS 00:19:00 The Hosts File 00:04:00 Net Command 00:08:00 Windows Name Resolution 00:11:00 Dynamic DNS 00:05:00 DNS Troubleshooting 00:13:00 Section 11: Securing TCP/IP Making TCP/IP Secure 00:04:00 Symmetric Encryption 00:06:00 Asymmetric Encryption 00:03:00 Cryptographic Hashes 00:05:00 Identification 00:12:00 Access Control 00:04:00 AAA 00:05:00 Kerberos/EAP 00:08:00 Single Sign-On 00:10:00 Certificates and Trust 00:14:00 Certificate Error Scenarios 00:08:00 Section 12: Advanced Networking Devices Understanding IP Tunneling 00:06:00 Virtual Private Networks 00:13:00 Introduction to VLANs 00:12:00 InterVLAN Routing 00:03:00 Interfacing with Managed Switches 00:11:00 Switch Port Protection 00:07:00 Port Bonding 00:07:00 Port Mirroring 00:04:00 Quality of Service 00:05:00 IDS vs. IPS 00:04:00 Proxy Servers 00:13:00 Load Balancing 00:09:00 Device Placement Scenarios 00:13:00 Section 13: IPv6 Introduction to IPv6 00:13:00 IPv6 Addressing 00:15:00 IPv6 in Action 00:13:00 IPv4 and IPv6 Tunneling 00:05:00 Section 14: Remote Connectivity Telephony Technologies 00:09:00 Optical Carriers 00:03:00 Packet Switching 00:05:00 Connecting with Dial-up 00:05:00 Digital Subscriber Line (DSL) 00:05:00 Connecting with Cable Modems 00:04:00 Connecting with Satellites 00:03:00 ISDN and BPL 00:04:00 Remote Desktop Connectivity 00:05:00 Advanced Remote Control Systems 00:09:00 Section 15: Wireless Networking Introduction to 802.11 00:12:00 802.11 Standards 00:12:00 Power over Ethernet (PoE) 00:04:00 Antennas 00:09:00 Wireless Security Standards 00:16:00 Implementing Wireless Security 00:07:00 Threats to Your Wireless Network 00:07:00 Retro Threats 00:05:00 Wi-Fi Protected Setup (WPS) 00:05:00 Enterprise Wireless 00:06:00 Installing a Wireless Network 00:15:00 Wireless Scenarios 00:07:00 More Wireless Scenarios 00:09:00 Section 16: Virtualization and Cloud Computing Virtualization Basics 00:07:00 Cloud Ownership 00:03:00 Cloud Implementation 00:12:00 Your First Virtual Machine 00:09:00 NAS and SAN 00:16:00 Platform as a Service (PaaS) 00:09:00 Software as a Service (SaaS) 00:03:00 Infrastructure as a Service (IaaS) 00:10:00 Section 17: Mobile Networking Cellular Technologies 00:05:00 Mobile Connectivity 00:07:00 Deploying Mobile Devices 00:05:00 Mobile Access Control 00:06:00 Section 18: Building a Real-World Network Network Types 00:04:00 Network Design 00:10:00 Power Management 00:06:00 Unified Communications 00:11:00 Network Documentation 00:07:00 Contingency Planning 00:10:00 Predicting Hardware Failure 00:05:00 Backups 00:08:00 Section 19: Managing Risk What is Risk Management? 00:06:00 Security Policies 00:08:00 Change Management 00:07:00 User Training 00:03:00 Standard Business Documentation 00:05:00 Mitigating Network Threats 00:05:00 High Availability 00:05:00 Section 20: Protecting Your Network Denial of Service 00:09:00 Malware 00:10:00 Social Engineering 00:04:00 Access Control 00:08:00 Man-in-the-Middle 00:22:00 Introduction to Firewalls 00:05:00 Firewalls 00:10:00 DMZ 00:06:00 Hardening Devices 00:14:00 Physical Security Controls 00:09:00 Testing Network Security 00:08:00 Network Protection Scenarios 00:14:00 Section 21: Network Monitoring SNMP 00:15:00 Documenting Logs 00:09:00 System Monitoring 00:08:00 SIEM (Security Information and Event Management) 00:07:00 Section 22: Network Troubleshooting Network Troubleshooting Theory 00:05:00

Overview Caring for adults combines compassion, skill, and dedication, creating a profound impact on individuals and communities. Providing support and helping people live independently, professionals in adult nursing and social care play a key role in improving lives. If you're passionate about making a difference, our Adult Nursing & Social Care Training is your gateway to a rewarding and meaningful career in care. This thoughtfully designed course offers a deep dive into key aspects of nursing and adult care, including safeguarding practices, personal care, and effective support strategies tailored to individual needs. Through engaging modules, you'll also develop vital skills in communication, record keeping, and promoting independence. By completing this training, you'll position yourself as a strong candidate in the nursing and care sector, opening doors to various opportunities. So enroll in this course today to fast-track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Description Begin your journey with Apex Learning today! The Adult Nursing & Social Care Training course teaches basic to advanced skills, helping you build a rewarding career in care. Strengthen your skills and knowledge in adult nursing and social care. Equip yourself with the tools to offer outstanding support and reach your career goals. Course curriculum 27 sections • 27 lectures • 13hrs (approx.) •Introduction to Nursing •Working in Different Healthcare Settings for Adult Nursing •Understanding legal, professional standards of practice and ethical aspects of health care - Part 1 •Understanding legal, professional standards of practice and ethical aspects of health care - Part 2 •Effective Communication in Adult Nursing •Health and Safety in Adult Nursing •Hygiene in Adult Nursing •Infection Control in Adult Nursing •Asepsis in Adult Nursing •Medication Administration in Nursing •Adult Care in Different Life Stages •Understanding Immune System in Adult Nursing •Rest and Sleep Management in Adult Nursing •Mobility and Immobility Issues of Patients in Adult Nursing •Pain Management for Adult Nursing •Nutrition in Adult Nursing •Fluid and Electrolyte Balance in Adult Nursing •Assisting with Elimination in Adult Nursing •Oxygenation in Adult Nursing •An Overview of Social Work •Social Work Basics •Theories of Social Work and Sociology •Teamwork and Casework Process Adult Nursing and Social Care •Dimensions of Social Work and Models of Intervention •Practice Contexts and Application in Adult Nursing and Social Work •Working with Adults •Social Worker Guidelines and the Role of a Social Worker Who is This course for? There is no experience or previous qualifications required for enrolment on this Adult Nursing & Social Care Training. It is available to all students, of all academic backgrounds. Requirements Our Adult Nursing & Social Care Training is fully compatible with PCs, Macs, Laptops, Tablets, and Smartphone devices. This nursing course has been designed to be fully compatible with tablets and smartphones, allowing you to access your nursing training via Wi-Fi, 3G, or 4G. There is no time limit for completing this course, so it can be studied in your own time and at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. Having expertise from the Adult Nursing & Social Care Training will enhance your CV and open doors to various career opportunities in the care sector. Adult Care Worker Support Worker Care Coordinator Rehabilitation Assistant Residential Care Officer

Overview The UK sees 1.3 MILLION food poisoning cases annually, with 276 outbreaks reported by the FSA between 2015-2020, affecting nearly 10,000 people. As a food business owner, restaurant manager, or catering provider, these Food Hygiene risks aren’t just statistics; they’re a direct threat to your reputation, finances, and customer trust. The food industry has no margin for error. Just one incident of foodborne illness can trigger a chain reaction of devastating consequences: irreversible damage to your reputation, crippling legal action under the Food Safety Act 1990, and most importantly, harm to the customers who trust you. In today’s regulated environment, where compliance is mandatory and scrutiny is intense, proper Food Hygiene and safety practices aren’t just best practice; they’re the foundation of a successful, sustainable food business. This comprehensive course on How to Improve Your Food Hygiene Rating will deepen your understanding of Food Hygiene. After successful completion of this Food Hygiene course you can acquire the required skills in this sector. This How to Improve Your Food Hygiene Rating comes with accredited certification which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. The How to Improve Your Food Hygiene Rating course provides the essential knowledge and skills to protect your business and customers. So, get ready to prepare your business for success and safety in all aspects of food production and distribution. Why Choose this Food Hygiene Training? Get a Free CPD Accredited Certificate upon completion of Food Hygiene course Get a free student ID card with Food Hygiene Training The Food Hygiene is affordable and simple to understand This Food Hygiene course is entirely online, interactive lesson with voiceover audio Lifetime access to the Food Hygiene course materials The Food Hygiene comes with 24/7 tutor support How will I get my Food Hygiene certificate? You may have to take a quiz or a written test online during or after the Food Hygiene course. After successfully completing the Food Hygiene course, you will be eligible for the certificate. Who is this Food Hygiene course for? There is no experience or previous qualifications required for enrolment on this How to Improve Your Food Hygiene Rating. It is available to all students, of all academic backgrounds. Requirements Our How to Improve Your Food Hygiene Rating is fully compatible with PC's, Mac's, Laptop,Tablet and Smartphone devices. This Food Hygiene course has been designed to be fully compatible on tablets and smartphones so you can access your course on wifi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career path Having these various qualifications will increase the value in your CV and open you up to multiple sectors related to Food Hygiene. Course Curriculum 2 sections • 13 lectures • 06:08:00 total length •Module 01: The Food Hygiene Rating Scheme: 00:52:00 •Module 02: Personal Hygiene: 00:27:00 •Module 03: Contamination Hazards: 00:25:00 •Module 04: How to Control Contamination Hazards: 00:37:00 •Module 05: Food Preparation and Processing for Food Manufacturing: 00:25:00 •Module 06: Cleaning: 00:24:00 •Module 07: Waste Disposal, Cleaning and Disinfection: 00:32:00 •Module 08: Food Safety Management System: 00:41:00 •Module 09: Pest Management: 00:26:00 •Module 10: Food Premises and Equipment: The Design and Construction: 00:30:00 •Module 11: Supervision of Food Safety: 00:34:00 •Module 12: Food Safety Training for the Staff: 00:15:00 •Assignment - How to Improve Your Food Hygiene Rating: 00:00:00

Are you ready to be at the helm, steering the ship into a realm where data is the new gold? In the infinite world of data, where information spirals at breakneck speed, lies a universe rich in potential and discovery: the domain of Data Science and Visualisation. This 'Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3' course unravels the wonders of extracting meaningful insights using Python, the worldwide leading language of data experts. Harnessing the strength of Python, you'll delve deep into data analysis, experience the finesse of visualisation tools, and master the art of Machine Learning. The need to understand, interpret, and act on this data has become paramount, with vast amounts of data increasing the digital sphere. Envision a canvas where raw numbers are transformed into visually compelling stories, and machine learning models foretell future trends. This course provides a meticulous pathway for anyone eager to learn the data representation paradigms backed by Python's robust libraries. Dive into a curriculum rich with analytical explorations, visual artistry, and machine learning predictions. Learning Outcomes Understanding the foundations and functionalities of Python, focusing on its application in data science. Applying various Python libraries like NumPy and Pandas for effective data analysis. Demonstrating proficiency in creating detailed visual narratives using tools like matplotlib, Seaborn, and Plotly. Implementing Machine Learning algorithms in Python using scikit-learn, ranging from regression models to clustering techniques. Designing and executing a holistic data analysis and visualisation project, encapsulating all learned techniques. Exploring advanced topics, encompassing recommender systems and natural language processing with Python. Attaining the confidence to independently analyse complex data sets and translate them into actionable insights.   Video Playerhttps://studyhub.org.uk/wp-content/uploads/2021/03/Data-Science-and-Visualisation-with-Machine-Learning.mp400:0000:0000:00Use Up/Down Arrow keys to increase or decrease volume. Why buy this Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments are designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Who is this Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 course for? Aspiring data scientists aiming to harness the power of Python. Researchers keen to enrich their analytical and visualisation skills. Analysts aiming to add machine learning to their toolkit. Developers striving to integrate data analytics into applications. Business professionals desiring data-driven decision-making capabilities. Career path Data Scientist: £55,000 - £85,000 Per Annum Machine Learning Engineer: £60,000 - £90,000 Per Annum Data Analyst: £30,000 - £50,000 Per Annum Data Visualisation Specialist: £45,000 - £70,000 Per Annum Natural Language Processing Specialist: £65,000 - £95,000 Per Annum Business Intelligence Developer: £40,000 - £65,000 Per Annum Prerequisites This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 does not require you to have any prior qualifications or experience. You can just enrol and start learning. This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Endorsed Certificate of Achievement from the Quality Licence Scheme Learners will be able to achieve an endorsed certificate after completing the course as proof of their achievement. You can order the endorsed certificate for only £85 to be delivered to your home by post. For international students, there is an additional postage charge of £10. Endorsement The Quality Licence Scheme (QLS) has endorsed this course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the course has been reviewed and approved by the QLS and meets the highest quality standards. Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. Course Curriculum Welcome, Course Introduction & overview, and Environment set-up Welcome & Course Overview 00:07:00 Set-up the Environment for the Course (lecture 1) 00:09:00 Set-up the Environment for the Course (lecture 2) 00:25:00 Two other options to setup environment 00:04:00 Python Essentials Python data types Part 1 00:21:00 Python Data Types Part 2 00:15:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1) 00:16:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2) 00:20:00 Python Essentials Exercises Overview 00:02:00 Python Essentials Exercises Solutions 00:22:00 Python for Data Analysis using NumPy What is Numpy? A brief introduction and installation instructions. 00:03:00 NumPy Essentials - NumPy arrays, built-in methods, array methods and attributes. 00:28:00 NumPy Essentials - Indexing, slicing, broadcasting & boolean masking 00:26:00 NumPy Essentials - Arithmetic Operations & Universal Functions 00:07:00 NumPy Essentials Exercises Overview 00:02:00 NumPy Essentials Exercises Solutions 00:25:00 Python for Data Analysis using Pandas What is pandas? A brief introduction and installation instructions. 00:02:00 Pandas Introduction 00:02:00 Pandas Essentials - Pandas Data Structures - Series 00:20:00 Pandas Essentials - Pandas Data Structures - DataFrame 00:30:00 Pandas Essentials - Handling Missing Data 00:12:00 Pandas Essentials - Data Wrangling - Combining, merging, joining 00:20:00 Pandas Essentials - Groupby 00:10:00 Pandas Essentials - Useful Methods and Operations 00:26:00 Pandas Essentials - Project 1 (Overview) Customer Purchases Data 00:08:00 Pandas Essentials - Project 1 (Solutions) Customer Purchases Data 00:31:00 Pandas Essentials - Project 2 (Overview) Chicago Payroll Data 00:04:00 Pandas Essentials - Project 2 (Solutions Part 1) Chicago Payroll Data 00:18:00 Python for Data Visualization using matplotlib Matplotlib Essentials (Part 1) - Basic Plotting & Object Oriented Approach 00:13:00 Matplotlib Essentials (Part 2) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials (Part 3) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials - Exercises Overview 00:06:00 Matplotlib Essentials - Exercises Solutions 00:21:00 Python for Data Visualization using Seaborn Seaborn - Introduction & Installation 00:04:00 Seaborn - Distribution Plots 00:25:00 Seaborn - Categorical Plots (Part 1) 00:21:00 Seaborn - Categorical Plots (Part 2) 00:16:00 Seborn-Axis Grids 00:25:00 Seaborn - Matrix Plots 00:13:00 Seaborn - Regression Plots 00:11:00 Seaborn - Controlling Figure Aesthetics 00:10:00 Seaborn - Exercises Overview 00:04:00 Seaborn - Exercise Solutions 00:19:00 Python for Data Visualization using pandas Pandas Built-in Data Visualization 00:34:00 Pandas Data Visualization Exercises Overview 00:03:00 Panda Data Visualization Exercises Solutions 00:13:00 Python for interactive & geographical plotting using Plotly and Cufflinks Plotly & Cufflinks - Interactive & Geographical Plotting (Part 1) 00:19:00 Plotly & Cufflinks - Interactive & Geographical Plotting (Part 2) 00:14:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Overview) 00:11:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Solutions) 00:37:00 Capstone Project - Python for Data Analysis & Visualization Project 1 - Oil vs Banks Stock Price during recession (Overview) 00:15:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3) 00:17:00 Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview) 00:03:00 Python for Machine Learning (ML) - scikit-learn - Linear Regression Model Introduction to ML - What, Why and Types.. 00:15:00 Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff 00:15:00 scikit-learn - Linear Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Linear Regression Model Hands-on (Part 2) 00:19:00 Good to know! How to save and load your trained Machine Learning Model! 00:01:00 scikit-learn - Linear Regression Model (Insurance Data Project Overview) 00:08:00 scikit-learn - Linear Regression Model (Insurance Data Project Solutions) 00:30:00 Python for Machine Learning - scikit-learn - Logistic Regression Model Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificityetc. 00:10:00 scikit-learn - Logistic Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Logistic Regression Model - Hands-on (Part 2) 00:20:00 scikit-learn - Logistic Regression Model - Hands-on (Part 3) 00:11:00 scikit-learn - Logistic Regression Model - Hands-on (Project Overview) 00:05:00 scikit-learn - Logistic Regression Model - Hands-on (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn - K Nearest Neighbors Theory: K Nearest Neighbors, Curse of dimensionality . 00:08:00 scikit-learn - K Nearest Neighbors - Hands-on 00:25:00 scikt-learn - K Nearest Neighbors (Project Overview) 00:04:00 scikit-learn - K Nearest Neighbors (Project Solutions) 00:14:00 Python for Machine Learning - scikit-learn - Decision Tree and Random Forests Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging. 00:18:00 scikit-learn - Decision Tree and Random Forests - Hands-on (Part 1) 00:19:00 scikit-learn - Decision Tree and Random Forests (Project Overview) 00:05:00 scikit-learn - Decision Tree and Random Forests (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) Support Vector Machines (SVMs) - (Theory Lecture) 00:07:00 scikit-learn - Support Vector Machines - Hands-on (SVMs) 00:30:00 scikit-learn - Support Vector Machines (Project 1 Overview) 00:07:00 scikit-learn - Support Vector Machines (Project 1 Solutions) 00:20:00 scikit-learn - Support Vector Machines (Optional Project 2 - Overview) 00:02:00 Python for Machine Learning - scikit-learn - K Means Clustering Theory: K Means Clustering, Elbow method .. 00:11:00 scikit-learn - K Means Clustering - Hands-on 00:23:00 scikit-learn - K Means Clustering (Project Overview) 00:07:00 scikit-learn - K Means Clustering (Project Solutions) 00:22:00 Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) Theory: Principal Component Analysis (PCA) 00:09:00 scikit-learn - Principal Component Analysis (PCA) - Hands-on 00:22:00 scikit-learn - Principal Component Analysis (PCA) - (Project Overview) 00:02:00 scikit-learn - Principal Component Analysis (PCA) - (Project Solutions) 00:17:00 Recommender Systems with Python - (Additional Topic) Theory: Recommender Systems their Types and Importance 00:06:00 Python for Recommender Systems - Hands-on (Part 1) 00:18:00 Python for Recommender Systems - - Hands-on (Part 2) 00:19:00 Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) Natural Language Processing (NLP) - (Theory Lecture) 00:13:00 NLTK - NLP-Challenges, Data Sources, Data Processing .. 00:13:00 NLTK - Feature Engineering and Text Preprocessing in Natural Language Processing 00:19:00 NLTK - NLP - Tokenization, Text Normalization, Vectorization, BoW. 00:19:00 NLTK - BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes 00:13:00 NLTK - NLP - Pipeline feature to assemble several steps for cross-validation 00:09:00 Resources Resources - Data Science and Visualisation with Machine Learning 00:00:00 Order your QLS Endorsed Certificate Order your QLS Endorsed Certificate 00:00:00