223 Data Structure courses in Sheffield delivered On Demand

About Course Master the Fundamentals of Programming with Python Course Description Embark on an exciting journey into the world of programming with this comprehensive Python course, designed to equip you with the essential skills and knowledge to become a proficient Python programmer. Whether you're a complete beginner or seeking to enhance your existing Python skills, this course caters to all levels of expertise. What will be discussed in detail? Introduction to Python: Delve into the basics of Python programming, including variables, data types, operators, and control flow statements. Working with Data Types: Explore the fundamental data types in Python, including numbers, strings, booleans, and lists. Python Strings: Master the art of manipulating strings, including slicing, concatenation, and string formatting techniques. Python Lists: Discover the power of lists, one of Python's most versatile data structures, and learn how to create, access, modify, and iterate over lists. Python Casting and Input: Understand the concept of type casting and learn how to take user input from the console. Python Dictionary: Uncover the usefulness of dictionaries, another essential data structure in Python, and learn how to store and retrieve data using key-value pairs. Python Date and Time: Learn how to handle date and time operations in Python, including creating, formatting, and manipulating date and time objects. Python Loop Part 1: Master the 'for' loop, a fundamental looping construct in Python, to iterate over sequences and perform repetitive tasks. Python Loop Part 2: Expand your understanding of loops by exploring the 'while' loop, used to execute a block of code repeatedly while a condition remains true. Creating a Function: Discover the power of functions, reusable blocks of code that perform specific tasks, and learn how to define, call, and pass arguments to functions. Python OOP Part 1: Delve into the world of Object-Oriented Programming (OOP) with Python, and learn the concepts of classes, objects, inheritance, and polymorphism. Python OOP Part 2: Enhance your OOP skills by exploring advanced concepts such as abstract classes, multiple inheritance, and operator overloading. Python Advanced OOP Part 1: Discover more advanced OOP techniques, including class methods, static methods, and decorators. Python Advanced OOP Part 2: Master the concept of exception handling, a crucial aspect of robust programming, and learn how to handle errors and exceptions effectively. Error Handling: Understand the importance of error handling in Python programming and learn how to identify, handle, and prevent errors. Python File Handling: Learn how to read, write, and manipulate files in Python, enabling you to store and retrieve data from external sources. Python Modules: Explore the concept of modules, reusable code libraries, and discover how to import, use, and create your own modules. Why should you enroll into it? Gain a comprehensive understanding of Python programming: Master the fundamentals of Python programming, from basic syntax to advanced OOP concepts. Develop practical coding skills: Apply your theoretical knowledge to hands-on coding exercises, solidifying your understanding and building your confidence. Prepare for a career in programming: Equip yourself with the essential skills required for entry-level programming positions. Enhance your problem-solving abilities: Learn to think algorithmically and develop effective problem-solving techniques using Python programming. Expand your skillset and knowledge: Whether you're a beginner or an experienced programmer, this course will broaden your understanding of Python and its capabilities. What will be taught? (Learning Outcomes/Learning Objectives) Understand the fundamental concepts of Python programming Work with different data types, including numbers, strings, lists, dictionaries, and Booleans Master control flow statements such as 'if', 'elif', and 'else' Create and manipulate Python functions Implement Object-Oriented Programming (OOP) concepts using classes, objects, inheritance, and polymorphism Handle errors and exceptions effectively Read, write, and manipulate files in Python Import, use, and create Python modules What Will You Learn? Understand the fundamental concepts of Python programming Work with different data types, including numbers, strings, lists, dictionaries, and Booleans Master control flow statements such as 'if', 'elif', and 'else' Create and manipulate Python functions Implement Object-Oriented Programming (OOP) concepts using classes, objects, inheritance, and polymorphism Handle errors and exceptions effectively Read, write, and manipulate files in Python Import, use, and create Python modules Course Content Introduction to Python Introduction to Python Working with Data Types Working with Data Types Python Strings Python Strings Python List Python List Python Casting and Input Python Casting and Input Python Dictionary Python Dictionary Python Date and Time Python Date and Time Python Loop (Part - 1) Python Loop (Part - 1) Python Loop (Part - 2) Python Loop (Part - 2) Python While Loop Python While Loop Creating a Function Creating a Function Python OOP (Part - 1) Python OOP (Part - 1) Python OOP (Part - 2) Python OOP (Part - 2) Python Advanced OOP (Part - 1) Python Advanced OOP (Part - 1) Python Advanced OOP (Part - 2) Python Advanced OOP (Part - 2) Error Handling Error Handling Python File Handling Python File Handling Python Modules Python Modules A course by Uditha Bandara Microsoft Most Valuable Professional (MVP) RequirementsA basic understanding of computers and operating systemsA willingness to learn and practice codingA computer with internet access and the ability to install Python Audience Beginners with no prior programming experience Programmers seeking to transition to Python Individuals looking to enhance their programming skills and knowledge Anyone interested in pursuing a career in programming Audience Beginners with no prior programming experience Programmers seeking to transition to Python Individuals looking to enhance their programming skills and knowledge Anyone interested in pursuing a career in programming

Quality Guarantee: Promising training excellence, satisfaction gurantee Accredited by: CPD UK & Quality License Scheme Tutor Support: Unlimited support via email, till you complete the course Recognised Certification: Accepted by thousands of professional bodies Start Anytime: With 1 year access to the course materials Online Learning: Learn from anywhere, whenever you want This Data Mining Course - Business Intelligence will help you get knowledge about the fundamentals of data mining, data warehouse architecture and components of the data warehouse. This course at a glance Accredited by CPD UK Endorsed by Quality Licence Scheme Learn how to store and keep the data Understand the fundamentals of data mining Know what is the meaning of business intelligence Understand different types of charts Learn problem structure and decision support system Get acquainted with the characteristics of a good dashboard and link with the balance scorecard system Recognise the process of KPI development for using in the business intelligence dashboard Learn data warehouse architecture Know the components of the data warehouse Learn the basics of data mining Understand data mining applications Why Data Mining Course - Business Intelligence right for you? This Data Mining Course - Business Intelligence is designed by industry experts to provide the learners with a thorough understanding of the tools and techniques used in data mining business intelligence. This self-paced online course will also aid you with the process of storing and keeping the data safe. In addition to this, you will also get an introduction to the basics of data mining, data mining technique, data mining applications and much more. By the end of the course, you gain an understanding of the key aspects of data mining and business intelligence altogether. This career advancement online course will also help you to kickstart your career as a professional data analyst or business manager. Data Mining Course - Business Intelligence Details Accredited by CPD certificates are accepted by thousands of professional bodies and government regulators here in the UK and around the world. Many organisations look for employees with CPD requirements, which means, that by doing this course, you would be a potential candidate in your respective field.   The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. Course Curriculum Data Warehouse - How to We Store and Keep the Data What is the Meaning of Business Intelligence Starting Case in Understanding Bi Needs in Different Phase of Business Decision Making Process and Need of It Systems Problem Structure and Decision Support System Introduction to Business Intelligence Applications Dashboard & Presentation Systems Different Types of Charts and Their Usage in Bi Dashboards Characteristics of Good Dashboard and Link With Balance Score Card System Examples of Bad Design of Dashboards - You Should Avoid - Part 1 Examples of Bad Design of Dashboards - You Must Avoid Process of Kpi Development for Using in Business Intelligence Dashboard Fundamentals of Data Mining and Process Overview of Data Warehouse More Detailed Explanation of Data Warehouse and Steps in Processing Data Warehouse Architecture - Tiers Components of Data Warehouse Approach to Develop Data Structure and Models of Database Business Intelligence and Dashboard Basics of Data Mining - Meaning Basics of Data Mining - Stages of Dm Data Mining Technique - Classification Data Mining - Clustering Data Mining - Association Rules Data Mining Applications - Banking Data Mining Applications - CRM Data Mining Applications - Other Industries Who should take this course? This comprehensive Data Mining - Business Intelligence course is suitable for anyone looking to improve their job prospects or aspiring to accelerate their career in this sector and want to gain in-depth knowledge of business intelligence and data mining methods. Entry Requirements There are no academic entry requirements for this Data Mining - Business Intelligence course, and it is open to students of all academic backgrounds. However, you are required to have a laptop/desktop/tablet or smartphone and a good internet connection. Assessment Method This Data Mining - Business Intelligence course assesses learners through multiple-choice questions (MCQs). Upon successful completion of the modules, learners must answer MCQs to complete the assessment procedure. Through the MCQs, it is measured how much a learner can grasp from each section. In the assessment pass mark is 60%. Certification Endorsed Certificate from Quality Licence Scheme After successfully passing the MCQ exam you will be eligible to order the Endorsed Certificate by Quality Licence Scheme. The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. It will give you a competitive advantage in your career, making you stand out from all other applicants and employees. There is a Quality Licence Scheme endorsement fee to obtain an endorsed certificate which is £65. Certificate of Achievement from Lead Academy After successfully passing the MCQ exam you will be eligible to order your certificate of achievement as proof of your new skill. The certificate of achievement is an official credential that confirms that you successfully finished a course with Lead Academy. Certificate can be obtained in PDF version at a cost of £12, and there is an additional fee to obtain a printed copy certificate which is £35. FAQs Is CPD a recognised qualification in the UK? CPD is globally recognised by employers, professional organisations and academic intuitions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement. CPD-certified certificates are accepted by thousands of professional bodies and government regulators here in the UK and around the world. Are QLS courses recognised? Although QLS courses are not subject to Ofqual regulation, they must adhere to an extremely high level that is set and regulated independently across the globe. A course that has been approved by the Quality Licence Scheme simply indicates that it has been examined and evaluated in terms of quality and fulfils the predetermined quality standards. When will I receive my certificate? For CPD accredited PDF certificate it will take 24 hours, however for the hardcopy CPD certificate takes 5-7 business days and for the Quality License Scheme certificate it will take 7-9 business days. Can I pay by invoice? Yes, you can pay via Invoice or Purchase Order, please contact us at info@lead-academy.org for invoice payment. Can I pay via instalment? Yes, you can pay via instalments at checkout. How to take online classes from home? Our platform provides easy and comfortable access for all learners; all you need is a stable internet connection and a device such as a laptop, desktop PC, tablet, or mobile phone. The learning site is accessible 24/7, allowing you to take the course at your own pace while relaxing in the privacy of your home or workplace. Does age matter in online learning? No, there is no age limit for online learning. Online learning is accessible to people of all ages and requires no age-specific criteria to pursue a course of interest. As opposed to degrees pursued at university, online courses are designed to break the barriers of age limitation that aim to limit the learner's ability to learn new things, diversify their skills, and expand their horizons. When I will get the login details for my course? After successfully purchasing the course, you will receive an email within 24 hours with the login details of your course. Kindly check your inbox, junk or spam folder, or you can contact our client success team via info@lead-academy.org

Register on the Business Intelligence and Data Mining today and build the experience, skills and knowledge you need to enhance your development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career. The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials. Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get a digital certificate as a proof of your course completion. The Business Intelligence and Data Mining is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablet, and smartphones. The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly! Why Choose this Course Earn a digital Certificate upon successful completion. Accessible, informative modules taught by expert instructors Study in your own time, at your own pace, through your computer tablet or mobile device Benefit from instant feedback through mock exams and multiple-choice assessments Get 24/7 help or advice from our email and live chat teams Full Tutor Support on Weekdays Course Design The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of- Video lessons Online study supplies Assignment Certificate of Achievement Endorsed Certificate of Achievement from the Quality Licence Scheme Once the course has been completed and the assessment has been passed, all students are entitled to receive an endorsed certificate. This will provide proof that you have completed your training objectives, and each endorsed certificate can be ordered and delivered to your address for only £99. Please note that overseas students may be charged an additional £10 for postage. CPD Certificate of Achievement from Janets Upon successful completion of the course, you will be able to obtain your course completion e-certificate free of cost. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99. Endorsement This course and/or training programme has been endorsed by the Quality Licence Scheme for its high-quality, non-regulated provision and training programmes. This course and/or training programme is not regulated by Ofqual and is not an accredited qualification. Your training provider will be able to advise you on any further recognition, for example progression routes into further and/or higher education. For further information please visit the Learner FAQs on the Quality Licence Scheme website. Method of Assessment In order to ensure the Quality Licensing scheme endorsed and CPD acknowledged certificate, learners need to score at least 60% pass marks on the assessment process. After submitting assignments, our expert tutors will evaluate the assignments and give feedback based on the performance. After passing the assessment, one can apply for a certificate. Who is this course for? The course is ideal for those who already work in this sector or are an aspiring expert. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a lesson to prove your newly-acquired knowledge. Course Content Business Intelligence and Data Mining Module 01: What is Business Intelligence? 00:05:00 Module 02: Starting Case in understanding BI needs in diff phase of business 00:07:00 Module 03: Decision Making Process and Need of IT systems 00:20:00 Module 04: Problem Structure and Decision Support System 00:11:00 Module 05: Introduction to BI Applications 00:18:00 Module 06: Dashboard presentation systems 00:07:00 Module 07: Different Types of Charts used in 131 Dashboards 00:30:00 Module 08: Good Dashboard and BSC 00:13:00 Module 09: Examples of Bad Dashboards 1 00:07:00 Module 10: Examples of Bad Dashboards 2 00:01:00 Module 11: Process of KPI Development 00:26:00 Module 12: Overview of Data warehouse 00:08:00 Module 13: More explaining of data warehouse and steps in processing 00:09:00 Module 14: Data Warehouse Architecture -Tiers 00:18:00 Module 15: Data Warehouse - components 00:15:00 Module 16: Approach to develop data structure and Models of database 00:16:00 Module 17: Basics of Data Mining - Meaning 00:35:00 Module 18: Basics of Data Mining - Stages of DM 00:25:00 Module 19: Data Mining Technique - Classification 00:07:00 Module 20: Data mining - Clustering 00:02:00 Module 21: Data Mining - Association Rules 00:05:00 Module 22: Data Mining Applications - Banking 00:03:00 Module 23: Data Mining Applications - CRM 00:04:00 Module 24: Data Mining Applications - other industries 00:04:00 Assignment Assignment - Business Intelligence and Data Mining 2 weeks, 1 day Order Your Certificate Order your Certificate QLS 00:00:00 Frequently Asked Questions Are there any prerequisites for taking the course? There are no specific prerequisites for this course, nor are there any formal entry requirements. All you need is an internet connection, a good understanding of English and a passion for learning for this course. Can I access the course at any time, or is there a set schedule? You have the flexibility to access the course at any time that suits your schedule. Our courses are self-paced, allowing you to study at your own pace and convenience. How long will I have access to the course? For this course, you will have access to the course materials for 1 year only. This means you can review the content as often as you like within the year, even after you've completed the course. However, if you buy Lifetime Access for the course, you will be able to access the course for a lifetime. Is there a certificate of completion provided after completing the course? Yes, upon successfully completing the course, you will receive a certificate of completion. This certificate can be a valuable addition to your professional portfolio and can be shared on your various social networks. Can I switch courses or get a refund if I'm not satisfied with the course? We want you to have a positive learning experience. If you're not satisfied with the course, you can request a course transfer or refund within 14 days of the initial purchase. How do I track my progress in the course? Our platform provides tracking tools and progress indicators for each course. You can monitor your progress, completed lessons, and assessments through your learner dashboard for the course. What if I have technical issues or difficulties with the course? If you encounter technical issues or content-related difficulties with the course, our support team is available to assist you. You can reach out to them for prompt resolution.

Master the art of project planning, scheduling, and resource management with Oracle Primavera P6 PPM Professional. The course offers a streamlined approach to efficiently manage projects and includes workshops for intermediate-level users to apply their knowledge in practice.

Register on the Learn DOM Manipulation with JavaScript today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career. The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials. Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get an e-certificate as proof of your course completion. The Learn DOM Manipulation with JavaScript is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablet, and smartphones. The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly! What You Get With The Learn DOM Manipulation with JavaScript Receive a e-certificate upon successful completion of the course Get taught by experienced, professional instructors Study at a time and pace that suits your learning style Get instant feedback on assessments 24/7 help and advice via email or live chat Get full tutor support on weekdays (Monday to Friday) Course Design The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of Video lessons Online study materials Certification Upon successful completion of the course, you will be able to obtain your course completion e-certificate free of cost. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99. Who Is This Course For: The course is ideal for those who already work in this sector or are an aspiring professional. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge. Requirements: The online training is open to all students and has no formal entry requirements. To study the Learn DOM Manipulation with JavaScript, all your need is a passion for learning, a good understanding of English, numeracy, and IT skills. You must also be over the age of 16.  Course Content Unit 01: Course Introduction What is the DOM? 00:02:00 Your first DOM update 00:05:00 Course Project: Code DOM Adventure 00:04:00 Unit 02: DOM Fundamentals HTML and the DOM 00:05:00 DOM standards 00:05:00 The BOM 00:04:00 The CSSOM 00:03:00 The tree (Data structure) 00:05:00 The DOM tree 00:11:00 The DOM and JavaScript 00:01:00 Unit 03: Code DOM Adventure App architecture 00:08:00 Challenge solution: The exit screen 00:04:00 App skeleton 00:05:00 The splash screen file 00:03:00 Download our asset kit now! 00:03:00 Including the assets 00:03:00 Unit 04: Creating elements Wiring the splash screen element 00:02:00 Creating elements at runtime 00:03:00 Appending HTML strings width append() 00:02:00 Appending nodes with append or append Child 00:03:00 Script order matters 00:04:00 Unit 05: Dynamic CSS Specifying classes to elements 00:04:00 Working with static styles 00:04:00 Defining styles at runtime 00:04:00 Querying the DOM to find elements 00:05:00 Unit 06: Profiling the pixel pipeline The pixel pipeline 00:02:00 Identifying bad practices 00:04:00 Profiling runtime performance 00:04:00 Batching DOM updates with document fragments 00:05:00 Too many nodes 00:04:00 Unit 07: Animation using DOM changes Removing nodes from the DOM 00:06:00 The animation frames 00:06:00 Our animate method 00:04:00 Our working animation! 00:06:00 Stopping the animation 00:08:00 Unit 08: Planning DOM changes with a state model Let's build the level! 00:02:00 2. Our state model to control the DOM from state. 00:10:00 Normalizing attributes 00:04:00 Our level class 00:04:00 Arrays, references and non-iterable empty slots 00:05:00 Building our state with an ugly oneliner 00:05:00 Module 04: The Language of Coaching 01:00:00 Write code for humans and normalize your code 00:05:00 Rendering the level element 00:05:00 Things are getting messy 00:06:00 Unit 09: Easy bundling Easy bundling 00:06:00 Bundle with the start script 00:01:00 Our dev server 00:02:00 Let's use DOMContentLoaded and ES Modules (ESM) 00:07:00 Dynamic style elements with CSS as ESM imports 00:04:00 Unit 10: DOM updates with basic state driven development Designing the shape of our state 00:02:00 Initializing our state in preparation to render DOM elements 00:05:00 DOM updates from state 00:08:00 Updates to state are reflected in the DOM 00:03:00 Modeling and render our chip walls 00:06:00 Unit 11: The player, Interacting with user input The player - Tech approach 00:02:00 Rendering the player with the DOM 00:07:00 Box model and global styles 00:06:00 Manipulating inline styles with the DOM 00:04:00 Moving the player by changing its state 00:06:00 DOM keyboard event listeners 00:07:00 Mapping and filtering DOM events data 00:04:00 Can the player move? - Tech approach 00:03:00 Preventing overlapping DOM elements 00:12:00 Prepare interactive frames 00:08:00 Resetting className and adding interactive frames on DOM events 00:06:00 Update frames without moving the element on DOM events 00:03:00 Unit 12: Interactive DOM, breaking walls Adding random DOM elements 00:06:00 DOM events when pressing the space key 00:05:00 Creating elements on DOM events 00:05:00 z-index manifest 00:04:00 Dynamic element IDs with the DOM 00:07:00 Interacting with other elements using the state model 00:06:00 Remove surrounding walls 00:04:00 Unit 13: Portal to exit the game Adding the portal to the screen 00:07:00 Random elements on the screen 00:05:00 Grouping inline CSS DOM updates 00:03:00 Exiting the game, when two elements cross paths 00:04:00 Challenge, your turn to build the exit screen 00:03:00 Challenge solution, my turn to build the exit screen 00:04:00 Hiding the portal behind a wall 00:05:00 Removing DOM event listeners 00:04:00 Unit 14: Animating all the things Rendering the splash screen 00:04:00 Swapping screens 00:02:00 Animating the portal 00:04:00 CSS kit - animations 00:03:00 Request animation frame and delaying animations 00:09:00 Animating with a parent css class 00:03:00 Old TV effect 00:02:00 Animating with delayed animation 00:11:00 Optimizing frames 00:03:00 Final frame optimizations 00:04:00 Unit 15: DOM Sound effects Dynamic audio elements 00:07:00 Interactive sound effects with DOM events 00:04:00 Delayed audio effects with callbacks and DOM events 00:04:00 Final lecture, final sound effect! exiting the game 00:03:00

Overview Mastering data science skills and expertise can open new doors of opportunities for you in a wide range of fields. Learn the fundamentals and develop a solid grasp of Python data science with the comprehensive Data Science with Python course. This course is designed to assist you in securing a valuable skill set and boosting your career. This course will provide you with quality training on the fundamentals of data analysis with Python. From the step-by-step learning process, you will learn the techniques of setting up the system. Then the course will teach you Python data structure and functions. You will receive detailed lessons on NumPy, Matplotlib, and Pandas. Furthermore, you will develop the skills for Algorithm Evaluation Techniques, visualising datasets and much more. After completing the course you will receive a certificate of achievement. This certificate will help you create an impressive resume. So join today! 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. Who is This course for? This course Data Science with Python course is ideal for beginners in data science. It will help them develop a solid grasp of Python and help them pursue their dream career in the field of data science. Requirements The students will not require any formal qualifications or previous experience to enrol in this course. Anyone can learn from the course anytime from anywhere through smart devices like laptops, tabs, PC, and smartphones with stable internet connections. They can complete the course according to their preferable pace so, there is no need to rush. Career Path This course will equip you with valuable knowledge and effective skills in this area. After completing the course, you will be able to explore career opportunities in the fields such as Data Analyst Data Scientist Data Manager Business Analyst And much more! Course Curriculum 90 sections • 90 lectures • 10:19:00 total length •Course Overview & Table of Contents: 00:09:00 •Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types: 00:05:00 •Introduction to Machine Learning - Part 2 - Classifications and Applications: 00:06:00 •System and Environment preparation - Part 1: 00:04:00 •System and Environment preparation - Part 2: 00:06:00 •Learn Basics of python - Assignment 1: 00:10:00 •Learn Basics of python - Assignment 2: 00:09:00 •Learn Basics of python - Functions: 00:04:00 •Learn Basics of python - Data Structures: 00:12:00 •Learn Basics of NumPy - NumPy Array: 00:06:00 •Learn Basics of NumPy - NumPy Data: 00:08:00 •Learn Basics of NumPy - NumPy Arithmetic: 00:04:00 •Learn Basics of Matplotlib: 00:07:00 •Learn Basics of Pandas - Part 1: 00:06:00 •Learn Basics of Pandas - Part 2: 00:07:00 •Understanding the CSV data file: 00:09:00 •Load and Read CSV data file using Python Standard Library: 00:09:00 •Load and Read CSV data file using NumPy: 00:04:00 •Load and Read CSV data file using Pandas: 00:05:00 •Dataset Summary - Peek, Dimensions and Data Types: 00:09:00 •Dataset Summary - Class Distribution and Data Summary: 00:09:00 •Dataset Summary - Explaining Correlation: 00:11:00 •Dataset Summary - Explaining Skewness - Gaussian and Normal Curve: 00:07:00 •Dataset Visualization - Using Histograms: 00:07:00 •Dataset Visualization - Using Density Plots: 00:06:00 •Dataset Visualization - Box and Whisker Plots: 00:05:00 •Multivariate Dataset Visualization - Correlation Plots: 00:08:00 •Multivariate Dataset Visualization - Scatter Plots: 00:05:00 •Data Preparation (Pre-Processing) - Introduction: 00:09:00 •Data Preparation - Re-scaling Data - Part 1: 00:09:00 •Data Preparation - Re-scaling Data - Part 2: 00:09:00 •Data Preparation - Standardizing Data - Part 1: 00:07:00 •Data Preparation - Standardizing Data - Part 2: 00:04:00 •Data Preparation - Normalizing Data: 00:08:00 •Data Preparation - Binarizing Data: 00:06:00 •Feature Selection - Introduction: 00:07:00 •Feature Selection - Uni-variate Part 1 - Chi-Squared Test: 00:09:00 •Feature Selection - Uni-variate Part 2 - Chi-Squared Test: 00:10:00 •Feature Selection - Recursive Feature Elimination: 00:11:00 •Feature Selection - Principal Component Analysis (PCA): 00:09:00 •Feature Selection - Feature Importance: 00:06:00 •Refresher Session - The Mechanism of Re-sampling, Training and Testing: 00:12:00 •Algorithm Evaluation Techniques - Introduction: 00:07:00 •Algorithm Evaluation Techniques - Train and Test Set: 00:11:00 •Algorithm Evaluation Techniques - K-Fold Cross Validation: 00:09:00 •Algorithm Evaluation Techniques - Leave One Out Cross Validation: 00:05:00 •Algorithm Evaluation Techniques - Repeated Random Test-Train Splits: 00:07:00 •Algorithm Evaluation Metrics - Introduction: 00:09:00 •Algorithm Evaluation Metrics - Classification Accuracy: 00:08:00 •Algorithm Evaluation Metrics - Log Loss: 00:03:00 •Algorithm Evaluation Metrics - Area Under ROC Curve: 00:06:00 •Algorithm Evaluation Metrics - Confusion Matrix: 00:10:00 •Algorithm Evaluation Metrics - Classification Report: 00:04:00 •Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction: 00:06:00 •Algorithm Evaluation Metrics - Mean Absolute Error: 00:07:00 •Algorithm Evaluation Metrics - Mean Square Error: 00:03:00 •Algorithm Evaluation Metrics - R Squared: 00:04:00 •Classification Algorithm Spot Check - Logistic Regression: 00:12:00 •Classification Algorithm Spot Check - Linear Discriminant Analysis: 00:04:00 •Classification Algorithm Spot Check - K-Nearest Neighbors: 00:05:00 •Classification Algorithm Spot Check - Naive Bayes: 00:04:00 •Classification Algorithm Spot Check - CART: 00:04:00 •Classification Algorithm Spot Check - Support Vector Machines: 00:05:00 •Regression Algorithm Spot Check - Linear Regression: 00:08:00 •Regression Algorithm Spot Check - Ridge Regression: 00:03:00 •Regression Algorithm Spot Check - Lasso Linear Regression: 00:03:00 •Regression Algorithm Spot Check - Elastic Net Regression: 00:02:00 •Regression Algorithm Spot Check - K-Nearest Neighbors: 00:06:00 •Regression Algorithm Spot Check - CART: 00:04:00 •Regression Algorithm Spot Check - Support Vector Machines (SVM): 00:04:00 •Compare Algorithms - Part 1 : Choosing the best Machine Learning Model: 00:09:00 •Compare Algorithms - Part 2 : Choosing the best Machine Learning Model: 00:05:00 •Pipelines : Data Preparation and Data Modelling: 00:11:00 •Pipelines : Feature Selection and Data Modelling: 00:10:00 •Performance Improvement: Ensembles - Voting: 00:07:00 •Performance Improvement: Ensembles - Bagging: 00:08:00 •Performance Improvement: Ensembles - Boosting: 00:05:00 •Performance Improvement: Parameter Tuning using Grid Search: 00:08:00 •Performance Improvement: Parameter Tuning using Random Search: 00:06:00 •Export, Save and Load Machine Learning Models : Pickle: 00:10:00 •Export, Save and Load Machine Learning Models : Joblib: 00:06:00 •Finalizing a Model - Introduction and Steps: 00:07:00 •Finalizing a Classification Model - The Pima Indian Diabetes Dataset: 00:07:00 •Quick Session: Imbalanced Data Set - Issue Overview and Steps: 00:09:00 •Iris Dataset : Finalizing Multi-Class Dataset: 00:09:00 •Finalizing a Regression Model - The Boston Housing Price Dataset: 00:08:00 •Real-time Predictions: Using the Pima Indian Diabetes Classification Model: 00:07:00 •Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset: 00:03:00 •Real-time Predictions: Using the Boston Housing Regression Model: 00:08:00 •Resources - Data Science & Machine Learning with Python: 00:00:00

12 in 1 Career Guided Programme | Python, Data Science, ML, Tableau, SQL Programming, Data Mining, Business Analysis | 130 CPD Points | Tutor Support | Lifetime Access

This second-edition JavaScript course covers fundamental concepts, including variables, data types, functions, and control flow, as well as advanced topics such as object-oriented programming, modules, and testing. With practical projects and clear explanations, learners can gain a solid understanding of the language and develop their skills.

This is a comprehensive course designed to provide a solid foundation in web development principles and practices. This course is intentionally structured to provide a technical understanding of web development concepts without delving into intricate implementation details. Anyone looking to better understand how web applications are built can take this course.

Scala is doubtless one of the most in-demand skills for data scientists and data engineers. This competitive course will teach you the essential concepts and methodologies of Scala with a lot of practical implementations.