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Dive deep into the vast realm of Python data science with our meticulously crafted course: 'Python Data Science with Numpy, Pandas and Matplotlib'. Explore the intricate details of Python, setting the stage with Pandas and Numpy, before delving into the power of Python data structures. With topics ranging from Python Strings to Matplotlib Histograms, you'll gain a holistic insight, ensuring that every dataset you touch unveils its story compellingly. So, if you're keen on transmuting raw data into visual masterpieces or insights, this journey is tailor-made for you. Learning Outcomes Grasp foundational knowledge of Python and its data structures like strings, lists, and dictionaries. Understand the potential of NumPy, from basic array operations to handling multi-dimensional arrays. Master the versatility of Pandas, encompassing everything from dataframe conversions to intricate operations like aggregation and binning. Efficiently manage, manipulate, and transform data using Pandas' diverse functionalities. Create visually striking and informative graphs using the power of Matplotlib. Why buy this Python Data Science with Numpy, Pandas and Matplotlib course? 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 Python Data Science with Numpy, Pandas and Matplotlib 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 Python Data Science with Numpy, Pandas and Matplotlib course for? Beginners eager to jumpstart their journey in Python data science. Analysts looking to enhance their data manipulation skills using Python. Statisticians keen on expanding their toolset with Python-based libraries. Data enthusiasts desiring a deep dive into Python's data libraries and structures. Professionals aiming to upgrade their data visualisation techniques. Prerequisites This Python Data Science with Numpy, Pandas and Matplotlib does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Python Data Science with Numpy, Pandas and Matplotlib 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 Data Scientist: £40,000 - £80,000 Python Developer: £35,000 - £70,000 Data Analyst: £30,000 - £55,000 Business Intelligence Analyst: £32,000 - £60,000 Research Analyst: £28,000 - £52,000 Data Visualization Engineer: £33,000 - £65,000 Course Curriculum Course Introduction and Table of Contents Course Introduction and Table of Contents 00:09:00 Introduction to Python, Pandas and Numpy Introduction to Python, Pandas and Numpy 00:07:00 System and Environment Setup System and Environment Setup 00:08:00 Python Strings Python Strings - Part 1 00:11:00 Python Strings - Part 2 00:09:00 Python Numbers and Operators Python Numbers and Operators - Part 1 00:06:00 Python Numbers and Operators - Part 2 00:07:00 Python Lists Python Lists - Part 1 00:05:00 Python Lists - Part 2 00:06:00 Python Lists - Part 3 00:05:00 Python Lists - Part 4 00:07:00 Python Lists - Part 5 00:07:00 Tuples in Python Tuples in Python 00:06:00 Sets in Python Sets in Python - Part 1 00:05:00 Sets in Python - Part 2 00:04:00 Python Dictionary Python Dictionary - Part 1 00:07:00 Python Dictionary - Part 2 00:07:00 NumPy Library - Introduction NumPy Library Intro - Part 1 00:05:00 NumPy Library Intro - Part 2 00:05:00 NumPy Library Intro - Part 3 00:06:00 NumPy Array Operations and Indexing NumPy Array Operations and Indexing - Part 1 00:04:00 NumPy Array Operations and Indexing - Part 2 00:06:00 NumPy Multi-Dimensional Arrays NumPy Multi-Dimensional Arrays - Part 1 00:07:00 NumPy Multi-Dimensional Arrays - Part 2 00:06:00 NumPy Multi-Dimensional Arrays - Part 3 00:05:00 Introduction to Pandas Series Introduction to Pandas Series 00:08:00 Introduction to Pandas Dataframes Introduction to Pandas Dataframes 00:07:00 Pandas Dataframe conversion and drop Pandas Dataframe conversion and drop - Part 1 00:06:00 Pandas Dataframe conversion and drop - Part 2 00:06:00 Pandas Dataframe conversion and drop - Part 3 00:07:00 Pandas Dataframe summary and selection Pandas Dataframe summary and selection - Part 1 00:06:00 Pandas Dataframe summary and selection - Part 2 00:06:00 Pandas Dataframe summary and selection - Part 3 00:07:00 Pandas Missing Data Management and Sorting Pandas Missing Data Management and Sorting - Part 1 00:07:00 Pandas Missing Data Management and Sorting - Part 2 00:07:00 Pandas Hierarchical-Multi Indexing Pandas Hierarchical-Multi Indexing 00:06:00 Pandas CSV File Read Write Pandas CSV File Read Write - Part 1 00:05:00 Pandas CSV File Read Write - Part 2 00:07:00 Pandas JSON File Read Write Pandas JSON File Read Write Operations 00:07:00 Pandas Concatenation Merging and Joining Pandas Concatenation Merging and Joining - Part 1 00:05:00 Pandas Concatenation Merging and Joining - Part 2 00:04:00 Pandas Concatenation Merging and Joining - Part 3 00:04:00 Pandas Stacking and Pivoting Pandas Stacking and Pivoting - Part 1 00:06:00 Pandas Stacking and Pivoting - Part 2 00:05:00 Pandas Duplicate Data Management Pandas Duplicate Data Management 00:07:00 Pandas Mapping Pandas Mapping 00:04:00 Pandas Grouping Pandas Groupby 00:06:00 Pandas Aggregation Pandas Aggregation 00:09:00 Pandas Binning or Bucketing Pandas Binning or Bucketing 00:08:00 Pandas Re-index and Rename Pandas Re-index and Rename - Part 1 00:04:00 Pandas Re-index and Rename - Part 2 00:05:00 Pandas Replace Values Pandas Replace Values 00:05:00 Pandas Dataframe Metrics Pandas Dataframe Metrics 00:07:00 Pandas Random Permutation Pandas Random Permutation 00:08:00 Pandas Excel sheet Import Pandas Excel sheet Import 00:07:00 Pandas Condition Selection and Lambda Function Pandas Condition Selection and Lambda Function - Part 1 00:05:00 Pandas Condition Selection and Lambda Function - Part 2 00:05:00 Pandas Ranks Min Max Pandas Ranks Min Max 00:06:00 Pandas Cross Tabulation Pandas Cross Tabulation 00:07:00 Matplotlib Graphs and plots Graphs and plots using Matplotlib - Part 1 00:06:00 Graphs and plots using Matplotlib - Part 2 00:02:00 Matplotlib Histograms Matplotlib Histograms 00:03:00 Resource File Resource File - Python Data Science with Numpy, Pandas and Matplotlib 00:00:00

Journalism is a noble and respective profession. Journalists bear the burden of presenting the crucial news and information to the mass people. If you want to build your career as a journalist or in the media industry, this journalism course can be the first step towards your professional journey. Learn the necessary skills you need to be a journalist from this Journalism course today. Our Journalism course lessons were prepared by experts and feature interactive activities. You'll learn how you can use various opportunities effectively from industry experts. This Journalism course has been divided into understandable and manageable sections that will help you grasp each concept- from the basic to advanced course components. Learn from industry experts today and enhance your skills and knowledge in no time. This Journalism course will increase your possibility to get your desired job and boost your personal growth. Learning Objectives Learn the basic principles of journalism Understand the roles and responsibilities of a journalist Familiarise with the ethical values and aspects of journalism Learn about various legal regulations and obligations Understand the language of journalism Be able to take notes fast and effectively Learn how to present your news attractively Grasp effective tips about data visualisation and presentation Who is this Course for? The Journalism course is ideal for highly aspiring individuals who wish to enhance their professional skills and train for the job they want! Also, this course is highly beneficial for people who want to have some in-depth knowledge on this topic and keep up to date with the latest information. So, you can enrol in this course if you are: Journalists Reporters Editors News Presenters News Researchers Study the Journalism course today and enhance your professional skillset from the comfort of your home! Entry Requirement There are no formal entry requirements for the Journalism course; with enrollment, this course is open to anyone! Anyone with a passion for learning about Journalism can enrol in this course without any hesitation. Although, the learner should be aged 16 or over to enrol in this course. Also, they need to have a good understanding of the English language to attend this course and understand what this course is about. CPD Certificate from Course Gate At the successful completion of the course, you can obtain your CPD certificate from us. You can order the PDF certificate for £4.99 and the hard copy for £9.99. Also, you can order both PDF and hardcopy certificates for £12.99. Career path This Journalism course will help you gain all the necessary theoretical knowledge to excel in the relevant field. Enrol on our Journalism course now and get started on the journey of taking your career to the next level. Course Curriculum Module 01: Introduction and Principles of Journalism Introduction and Principles of Journalism 00:18:00 Module 02: History and Development of Journalism History and Development of Newspaper Journalism 00:26:00 Module 03: Interviewing Interviewing 00:35:00 Module 04: Newspaper Journalism Newspaper Journalism 00:30:00 Module 05: News Writing, Production and Reporting News Writing, Production and Reporting 00:20:00 Module 06: Television Journalism Television Journalism 00:32:00 Module 07: Radio Journalism Radio Journalism 00:37:00 Module 08: Media Regulatory Bodies Media Regulatory Bodies 00:31:00 Module 09: Writing Skills for Journalists Writing Skills for Journalists 00:41:00 Module 10: Journalism law Journalism Law 00:35:00 Module 11: Defamation Defamation 00:20:00 Module 12: Journalism Ethics Journalism Ethics 00:17:00 Module 13: Health and Safety for Journalists Health and Safety for Journalists 00:38:00 Module 14: Niche Journalism Niche Journalism 00:24:00 Module 15: Tips on Writing a Good Feature Story Tips on Writing a Good Feature Story 00:34:00 Module 16: Online and Freelance Journalism Online and Freelance Journalism 00:16:00 Module 17: Becoming a Journalist Becoming a Journalist 00:29:00 Certificate and Transcript Order Your Certificates or Transcripts 00:00:00

Data Analysis: Data Analysis Training Have you ever wondered how companies get insights from massive volumes of data to stay competitive and make wise decisions? If so, then participate in our exclusive Data Analysis: Data Analysis Course. This Data Analysis Course describes the fundamentals of data, statistics, and an introduction to Data Analysis. How to get data and where to find it is explained in the Data Analysis Course. Moreover, this Data Analysis Course covers data cleansing, preprocessing, and exploratory data analysis (EDA). Additionally, the Data Analysis Course provides an introduction to Python and Excel for Data Analysis. This thorough Data Analysis Course includes lessons on data wrangling with Pandas (python) and data visualisation using Matplotlib and Seaborn (python). Enrol in our Data Analysis Course to study the fundamentals of statistical analysis and machine learning. Main Course: Data Analysis (Data Analytics) Training Free Courses included with Data Analysis: Data Analysis Training Course: Course 01: Minute Taking Course 02: GDPR Course 03: Cyber Security [ Note: Free PDF certificate as soon as completing the Data Analysis: Data Analysis Training Course] Data Analysis: Data Analysis Training Online This Data Analysis (Data Analytics) Training consists of 12 modules. Curriculum of Data Analysis (Data Analytics) Training Course Module 1: Introduction to Data Analytics Module 2: Basics of Data and Statistics Module 3: Data Collection and Sources Module 4: Data Cleaning and Preprocessing Module 5: Exploratory Data Analysis (EDA) Module 6: Introduction to Excel for Data Analytics Module 7: Introduction to Python for Data Analytics Module 8: Data Wrangling with Pandas (Python) Module 9: Data visualisation with Matplotlib and Seaborn (Python) Module 10: Introduction to Basic Statistical Analysis Module 11: Introduction to Machine Learning Module 12: Capstone Project - Exploratory Data Analysis Assessment Method of Data Analysis (Data Analytics) Training Course After completing Data Analysis: Data Analysis Training Course, you will get quizzes to assess your learning. You will do the later modules upon getting 60% marks on the quiz test. Apart from this, you do not need to sit for any other assessments. Certification of Data Analysis (Data Analytics) Training Course After completing the Data Analysis: Data Analysis Training Course, you can instantly download your certificate for FREE. The hard copy of the certification will also be delivered to your doorstep via post, which will cost £13.99. Who is this course for? Data Analysis: Data Analysis Training Online For business professionals, entrepreneurs, or anybody else looking to have a thorough grasp of data analysis in a commercial setting, this Data Analysis Course is ideal. Requirements Data Analysis: Data Analysis Training Online To enrol in this Data Analysis: Data Analysis Training Course, students must fulfil the following requirements: Good Command over English language is mandatory to enrol in our Data Analysis Training Course. Be energetic and self-motivated to complete our Data Analysis Training Course. Basic computer Skill is required to complete our Data Analysis Training Course. If you want to enrol in our Data Analysis Training Course, you must be at least 15 years old. Career path Data Analysis: Data Analysis Training Online This Data Analysis Course will assist you in obtaining positions as a business analyst, marketing analyst, data analysis, and in related fields.

Data Analysis: Data Analysis Course Would you like to acquire the skills and self-assurance necessary to make wise choices and successfully traverse the intricate and ever-changing realm of data analysis? Enrol in our Data Analysis Course. The fundamentals of data, statistics, and an introduction to data analysis are all covered in this data analysis course. The how-to of data collection and its sources are explained in the Data Analysis Course. This Data Analysis Course teaches preprocessing, data cleansing, and exploratory data analysis (EDA). An overview of Excel and Python for data analysis is explained in this Data Analysis Course. This extensive Data Analysis course includes lessons on data wrangling with Pandas (Python) and data visualisation using Matplotlib and Seaborn (Python). So, quickly join our Data Analysis Course to learn the fundamentals of machine learning and statistical analysis! Special Offers with free gifts for this Data Analysis: Data Analysis Course This Data Analysis Course course includes a FREE PDF Certificate. Lifetime access to this Data Analysis Course course Instant access to this Data Analysis Course course Get FREE Tutor Support to this Data Analysis Course Course Learning Outcome of Data Analysis Course This Data Analysis Course will help you learn about: Introduction to data analysis, basics of data, and statistics. Data Analysis Course explains how to collect data and its sources. Data cleaning, processing, and exploratory data analysis (EDA) are included in this Data Analysis Course. This Data Analysis Course describes an introduction to Excel for Data Analysis and Python for Data Analysis. Data Wrangling with Pandas (Python) and Data Visualisation with Matplotlib and Seaborn (Python) are parts of this comprehensive Data Analysis Course. With the help of this Data Analysis Course, you will learn the basics of statistical analysis and machine learning. Data Analysis: Data Analysis Course Embark on a transformative journey with our Data Analysis course, designed for beginners. Dive deep into the world of data analysis, mastering essential techniques and tools. Gain practical skills in Data Analysis, empowering you to unlock insights and drive informed decisions. Start your Data Analysis journey today! Who is this course for? Data Analysis: Data Analysis Course Anyone looking to have a thorough grasp of data analysis in a commercial setting should take this Data Analysis: Data Analysis Course. Requirements Data Analysis: Data Analysis Course To enrol in this Data Analysis: Data Analysis Course, students must fulfil the following requirements. To join in our Data Analysis: Data Analysis Course, you must have a strong command of the English language. To successfully complete our Data Analysis: Data Analysis Course, you must be vivacious and self driven. To complete our Data Analysis: Data Analysis Course, you must have a basic understanding of computers. A minimum age limit of 15 is required to enrol in this Data Analysis: Data Analysis Course. Career path Data Analysis: Data Analysis Course With the assistance of this Data Analysis Course, you can obtain work as a data analyst, business analyst, marketing analyst, or in related fields.

Dive into the intricate world of numbers and data with our comprehensive 'Microsoft Excel & Accounting Training' course. Begin your journey by mastering the foundational elements of Microsoft Office Excel 2016, from the basics of worksheet modifications to the art of data visualisation using charts. As you progress, pivot your attention towards the meticulous realm of accounting. Here, you'll unravel the secrets of the accounting equation, immerse yourself in transaction analyses, and culminate your learning by understanding the complete accounting cycle. Whether you're looking to enhance your data management skills or embark on a career in accounting, this course is your stepping stone to success. Learning Outcomes: Acquire proficiency in utilising Microsoft Excel 2016 for data analysis, visualisation, and workbook management. Understand the core principles of accounting, including the accounting equation and transaction analysis. Demonstrate the ability to prepare financial statements and complete the accounting cycle. Implement advanced Excel features such as PivotTables, PivotCharts, and Lookup Functions. Apply knowledge in real-world scenarios, including fiscal year evaluations and spreadsheet exercises. Why buy this Microsoft Excel & Accounting Training? 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 Microsoft Excel & Accounting Training 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 Microsoft Excel & Accounting Training course for? Individuals aiming to bolster their data analysis and management capabilities. Aspiring accountants keen on understanding the fundamentals of the profession. Business owners desiring a deeper grasp of financial statements and accounting cycles. Students pursuing a career in finance or data management. Professionals looking to integrate Excel functionalities into their daily tasks. Career path Data Analyst: Average salary range: £25,000 - £40,000 Annually Accountant: Average salary range: £28,000 - £52,000 Annually Financial Controller: Average salary range: £40,000 - £70,000 Annually Management Accountant: Average salary range: £30,000 - £55,000 Annually Excel Specialist: Average salary range: £22,000 - £35,000 Annually Bookkeeper: Average salary range: £18,000 - £30,000 Annually Prerequisites This Microsoft Excel & Accounting Training does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Microsoft Excel & Accounting Training 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 **Microsoft Excel** Getting Started with Microsoft Office Excel 2016 Navigate the Excel User Interfact 00:28:00 Use Excel Commands 00:10:00 Create and Save a Basic Workbook 00:19:00 Enter Cell Data 00:12:00 Use Excel Help 00:05:00 Performing Calculations Create Worksheet Formulas 00:15:00 Insert Functions 00:17:00 Reuse Formulas and Functions 00:17:00 Modifying a Worksheet Insert, Delete, and Adjust Cells, Columns, and Rows 00:10:00 Search for and Replace Data 00:09:00 Use Proofing and Research Tools 00:07:00 Formatting a Worksheet Apply Text Formats 00:16:00 Apply Number Format 00:07:00 Align Cell Contents 00:09:00 Apply Styles and Themes 00:12:00 Apply Basic Conditional Formatting 00:11:00 Create and Use Templates 00:08:00 Printing Workbooks Preview and Print a Workbook 00:10:00 Set Up the Page Layout 00:09:00 Configure Headers and Footers 00:07:00 Managing Workbooks Manage Worksheets 00:05:00 Manage Workbook and Worksheet Views 00:07:00 Manage Workbook Properties 00:06:00 Working with Functions Work with Ranges 00:18:00 Use Specialized Functions 00:11:00 Work with Logical Functions 00:23:00 Work with Date & Time Functions 00:08:00 Work with Text Functions 00:11:00 Working with Lists Sort Data 00:10:00 Filter Data 00:10:00 Query Data with Database Functions 00:09:00 Outline and Subtotal Data 00:09:00 Analyzing Data Create and Modify Tables 00:16:00 Apply Intermediate Conditional Formatting 00:07:00 Apply Advanced Conditional Formatting 00:05:00 Visualizing Data with Charts Create Charts 00:13:00 Modify and Format Charts 00:12:00 Use Advanced Chart Features 00:12:00 Using PivotTables and PivotCharts Create a PivotTable 00:13:00 Analyze PivotTable Data 00:12:00 Present Data with PivotCharts 00:07:00 Filter Data by Using Timelines and Slicers 00:11:00 Working with Multiple Worksheets and Workbooks Use Links and External References 00:12:00 Use 3-D References 00:06:00 Consolidate Data 00:05:00 Using Lookup Functions and Formula Auditing Use Lookup Functions 00:12:00 Trace Cells 00:09:00 Watch and Evaluate Formulas 00:08:00 Sharing and Protecting Workbooks Collaborate on a Workbook 00:19:00 Protect Worksheets and Workbooks 00:08:00 Automating Workbook Functionality Apply Data Validation 00:13:00 Search for Invalid Data and Formulas with Errors 00:04:00 Work with Macros 00:18:00 Creating Sparklines and Mapping Data Create Sparklines 00:07:00 MapData 00:07:00 Forecasting Data Determine Potential Outcomes Using Data Tables 00:08:00 Determine Potential Outcomes Using Scenarios 00:09:00 Use the Goal Seek Feature 00:04:00 Forecasting Data Trends 00:05:00 **Accounting Training** Professional Bookkeeper Introduction Professional Bookkeeper 00:09:00 Introduction to Accounting and Business Defining a Business 00:07:00 Ethics in Accounting 00:05:00 Generally Accepted Accounting Principles (GAAP) 00:10:00 The Accounting Equation The Accounting Equation 00:07:00 Transactions 00:11:00 Financial Statements 00:13:00 Analyzing Transactions The Accounting Equation and Transactions 00:16:00 Double-Entry System 00:11:00 Transactions - Journalizing 00:17:00 Journal Entries 00:38:00 Entering Information - Posting Entries Posting Entries 00:10:00 The Trial Balance 00:10:00 Finding Errors Using Horizontal Analysis 00:09:00 Horizontal Trend : Balance Sheet 00:21:00 Horizontal Trend: Income Statement 00:36:00 Adjusting Process The Purpose of the Adjusting Process 00:15:00 Adjusting Entries Adjusting Entries - Prepaid Expenses 00:13:00 Adjusting Entries - Accrued Revenues 00:10:00 Adjusting Entries - Depreciation Expense 00:09:00 Adjustment Summary Adjustment Summary - Review 00:13:00 Vertical Analysis 00:33:00 Preparing a Worksheet Preparing a Worksheet 00:06:00 Financial Statements The Income Statement 00:11:00 Financial Statements - Definitions 00:12:00 Completing the Accounting Cycle Temporary vs. Permanent Account 00:19:00 The Accounting Cycle Illustrated Accounting Cycle Illustrated - Steps 1-5 00:11:00 Accounting Cycle Illustrated - Steps 6-10 00:12:00 Fiscal Year Fiscal Year 00:09:00 Spreadsheet Exercise Spreadsheet Exercise - Steps 1-4 00:11:00 Spreadsheet Exercise - Steps 5-7 00:37:00

In this competitive job market, you need to have some specific skills and knowledge to start your career and establish your position. This Flourish Studio Masterclass : Create Animated Visualisation will help you understand the current demands, trends and skills in the sector. The course will provide you with the essential skills you need to boost your career growth in no time. The Flourish Studio Masterclass : Create Animated Visualisation will give you clear insight and understanding about your roles and responsibilities, job perspective and future opportunities in this field. You will be familiarised with various actionable techniques, career mindset, regulations and how to work efficiently. This course is designed to provide an introduction to Flourish Studio Masterclass : Create Animated Visualisation and offers an excellent way to gain the vital skills and confidence to work toward a successful career. It also provides access to proven educational knowledge about the subject and will support those wanting to attain personal goals in this area. Learning Objectives Learn the fundamental skills you require to be an expert Explore different techniques used by professionals Find out the relevant job skills & knowledge to excel in this profession Get a clear understanding of the job market and current demand Update your skills and fill any knowledge gap to compete in the relevant industry CPD accreditation for proof of acquired skills and knowledge Who is this Course for? Whether you are a beginner or an existing practitioner, our CPD accredited Flourish Studio Masterclass : Create Animated Visualisation is perfect for you to gain extensive knowledge about different aspects of the relevant industry to hone your skill further. It is also great for working professionals who have acquired practical experience but require theoretical knowledge with a credential to support their skill, as we offer CPD accredited certification to boost up your resume and promotion prospects. Entry Requirement Anyone interested in learning more about this subject should take this Flourish Studio Masterclass : Create Animated Visualisation. This course will help you grasp the basic concepts as well as develop a thorough understanding of the subject. The course is open to students from any academic background, as there is no prerequisites to enrol on this course. The course materials are accessible from an internet enabled device at anytime of the day. CPD Certificate from Course Gate At the successful completion of the course, you can obtain your CPD certificate from us. You can order the PDF certificate for £9 and the hard copy for £15. Also, you can order both PDF and hardcopy certificates for £22. Career path The Flourish Studio Masterclass : Create Animated Visualisation will help you to enhance your knowledge and skill in this sector. After accomplishing this course, you will enrich and improve yourself and brighten up your career in the relevant job market. Course Curriculum Introduction to Flourish Studio Welcome 00:04:00 Flourish Studio Background Story 00:01:00 Features of Flourish Studio 00:02:00 Flourish Studio Plans (Free, Business, Enterprise) 00:02:00 Getting Started with Flourish Signing up 00:02:00 Home Page Interface Walkthrough 00:06:00 Creating our First Flourish Visualisation 00:04:00 Adding and Managing Data in Flourish Templates Managing Data in Visualisations 00:08:00 Column Bindings 00:06:00 Merge Datasets 00:07:00 Creating Visualisations in Flourish Studio from scratch Creating a Bar or Line Chart in Flourish Studio - First Steps 00:08:00 Changing Settings to update Chart's look and feel - 1 00:21:00 Changing Settings to update Chart's look and feel - 2 00:10:00 Changing Settings to update Chart's look and feel - 3 00:12:00 More Visualisation Templates in Flourish Studio Table Charts (including mini visualisations) 00:09:00 Creating a Hierarchy Visualisation 00:05:00 Scatter Plot 00:06:00 More interesting variations of Scatter Plot 00:04:00 Map & Projection Charts + 3D Maps 00:08:00 Survey Charts 00:07:00 Gantt Chart 00:06:00 Radar Chart in Flourish Studio 00:06:00 Creating a Story and other Options How to create a Story in Flourish 00:13:00 Exporting, Publishing and Sharing 00:05:00 Flourish's Embed Options 00:06:00 How to Delete Projects 00:02:00 Other Exciting and Important Features Controlling access to Visualisations and stories with different Account Types 00:03:00 How to create a video or GIF from Flourish Visualisation/Story 00:04:00 How to generate the thumbnail of your visualisation 00:02:00 Customise colours in Flourish palettes 00:02:00 How to show published projects on your profile page 00:03:00 How to colour parts of your text with custom HTML 00:03:00 Add Social icons in Footer 00:02:00 Data Visualisation Tips & Resources How to select the right Visualisation Template 00:05:00 Dashboard Development Best Practices 00:04:00 Sources to get Datasets to use in Visualisations 00:02:00 Useful Resources to get Help & Continue Learning 00:06:00 Congratulations Congratulations on Course Completion 00:01:00 Certificate and Transcript Order Your Certificates or Transcripts 00:00:00

Learn how to create an automated trading bot using Python with this comprehensive course. Master Python basics, understand trading fundamentals, build and integrate the bot with a broker API, and run it effectively. Learning Outcomes: Gain proficiency in Python programming for trading purposes. Understand the fundamental concepts of trading and market dynamics. Build a structured trading bot using Python and Github version control. Integrate the bot with a broker API for real-time trading functionality. Successfully run and manage the automated trading bot for efficient execution. Why buy this Making Automated Trading Bot Using Python? 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 Making Automated Trading Bot Using Python 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 Making Automated Trading Bot Using Python 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 Making Automated Trading Bot Using Python does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Making Automated Trading Bot Using Python 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 Making Automated Trading Bot Using Python is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Section 01: Introduction About the course structure 00:05:00 Why working is important? 00:04:00 The free and perfect tools 00:07:00 Our editor: Atom 00:04:00 Version control: Github 00:07:00 Python download (Mac) 00:05:00 Python download (Windows) 00:02:00 Section 02: Python Basics for Trading Introduction 00:03:00 Python Libraries 00:05:00 Iterators: for 00:08:00 Iterators: while 00:08:00 Conditionals: if & else 00:10:00 Logic gates: and & or 00:09:00 Error handling: try & except 00:09:00 Functions and calls to libraries 00:13:00 Objects and classes (1) 00:10:00 Objects and classes (2) 00:07:00 Debugging the code 00:12:00 Closing and wrap up 00:01:00 Section 03: Trading Basics Introduction 00:03:00 Fundamental vs Technical Analysis 00:04:00 Stocks vs CFDs 00:05:00 Long and Short positions 00:04:00 Takeprofit and Stoploss 00:03:00 Setting a real Stoploss 00:08:00 Limit and Market orders 00:10:00 Don't forget the spread 00:04:00 Stock data visualisation: candles 00:08:00 Technical Indicators: about 00:05:00 Exponential Moving Average 00:08:00 EMA use and interpretation 00:06:00 Relative Strength Index 00:07:00 Stochastic Oscillator 00:09:00 Closing and wrap up 00:01:00 Section 04: Bot Code General Structure Introduction 00:02:00 Overview 00:08:00 The Entry Strategy 00:10:00 About Tradingview 00:12:00 When to enter (1) 00:08:00 When to enter (2) 00:08:00 Open and hold a position 00:12:00 Closing a position 00:08:00 Review (1) 00:06:00 Review (2) 00:13:00 Closing 00:02:00 Section 05: Github Basics Introduction 00:04:00 Download and install Github 00:01:00 Create a repo 00:10:00 Working with branches 00:13:00 Section 06: Building Your Bot Introduction 00:05:00 Create the first bot file 00:07:00 Building the bot scheme 00:08:00 Complete your code scheme (1) 00:11:00 Complete your code scheme (2) 00:11:00 Complete your code scheme (3) 00:18:00 A logger to remember (1) 00:14:00 A logger to remember (2) 00:14:00 Organising your code 00:07:00 Main function: run bot 00:23:00 Link the bot and the library 00:08:00 Traderlib control functions (1) 00:12:00 Traderlib control functions (2) 00:13:00 Check if tradable function 00:06:00 Set stoploss function 00:10:00 Set takeprofit function 00:04:00 Load historical data function 00:01:00 Get open positions function 00:04:00 Submit and cancel order functions 00:04:00 Check positions function 00:09:00 The Tulipy libraries 00:07:00 Importing all the libraries 00:03:00 First filter: get general trend 00:19:00 Second filter: get instant trend 00:14:00 Third filter: RSI 00:08:00 Fourth filter: Stochastic Oscillator 00:14:00 Enter position (1) 00:13:00 Enter position (2) 00:11:00 Enter position (3) 00:15:00 Enter position (4) 00:08:00 Last check before opening 00:13:00 Exit position and get out 00:10:00 Linking everything (1) 00:12:00 Linking everything (2) 00:12:00 Linking everything (3) 00:15:00 Fixing a mistake: going Short 00:05:00 Handling all your variables 00:18:00 Closing and wrap up 00:01:00 Run function scheme clarification and rebuild 00:13:00 Section 07: Integrating the Broker API Introduction 00:03:00 The Alpaca Python API Wrapper 00:07:00 Initialising the REST API 00:09:00 Running the program (crash!) 00:06:00 Integration with check account (1) 00:08:00 Integration with check account (2) 00:05:00 Clean open orders function 00:10:00 Importing the trading library 00:04:00 Running the main 00:05:00 Check position function 00:09:00 Check if asset exists function 00:08:00 Fetching barset data (theory) 00:07:00 Fetching barset data (practice) 00:12:00 Updating the code for the Alpaca API V2 (explanation) 00:03:00 Updating the code for the Alpaca API V2 (implementation) 00:08:00 Organizing data with Pandas 00:06:00 Get general trend function (1) 00:08:00 Reframing the timeframe with Pandas 00:23:00 Get general trend function (2) 00:13:00 Get instant trend function 00:08:00 Get RSI function 00:06:00 Get Stochastic function 00:10:00 Get current price function 00:05:00 Finishing get shares amount 00:09:00 Opening a position (1) 00:12:00 Opening a position (2) 00:09:00 Check the open position 00:07:00 Cancelling the order (1) 00:20:00 Cancelling the order (2) 00:08:00 Making sure we cancelled 00:03:00 Get average entry price function 00:10:00 Fixing bugs when getting price 00:18:00 Check Stochastic crossing 00:02:00 Holding an open position 00:11:00 Submitting the exit order 00:08:00 Closing position and out (1) 00:08:00 Closing position and out (2) 00:10:00 Closing and wrap up 00:01:00 Section 08: Running the Trading Bot Introduction 00:03:00 Filtering asset by price and volume 00:07:00 Get the bot ready to trade 00:04:00 Running the Trading Bot with AAPL 00:09:00 A real open position 00:08:00 Debugging and bug fixing 00:12:00 Fixing one (last) bug 00:02:00 Running the bot with TSLA 00:10:00 Discussing EMA implementations 00:12:00 Closing and wrap up 00:02:00

Microsoft Office skills are in high demand across industries, and proficiency in Microsoft Word, Microsoft Excel, Microsoft PowerPoint, and Microsoft Office 365 opens up numerous career opportunities. In the UK, administrative roles, data analysis positions, office management, project coordination, and marketing support roles are just a few examples of job prospects. With average salaries ranging from £20,000 to £45,000 per year, individuals with comprehensive Microsoft Office skills can secure stable employment and contribute to the success of various organisations. Enrol in the Ultimate Microsoft Office Skills Training course today and equip yourself with the knowledge and expertise needed to thrive in the ever-evolving workplace. You Will Learn Following Things: Develop a solid foundation in Microsoft Office applications, including Word, Excel, PowerPoint, and Office 365. 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Details Perks of Learning with IOMH One-to-one support from a dedicated tutor throughout your course. Study online - whenever and wherever you want. Instant Digital/ PDF certificate 100% money back guarantee 12 months access This course covers everything you must know to stand against the tough competition. The future is truly yours to seize with this Mastering Microsoft Office: Word, Excel, PowerPoint, and 365. Enrol today and complete the course to achieve a certificate that can change your career forever. Process of Evaluation After studying the course, your skills and knowledge will be tested with an MCQ exam or assignment. You have to get a score of 60% to pass the test and get your certificate. Certificate of Achievement After completing the Mastering Microsoft Office: Word, Excel, PowerPoint, and 365 course, you will receive your CPD-accredited Digital/PDF Certificate for £5.99. To get the hardcopy certificate for £12.99, you must also pay the shipping charge of just £3.99 (UK) and £10.99 (International). Who Is This Course for? This course is designed for individuals who want to enhance their Microsoft Office skills for personal or skilled purposes. Whether you are a student, an experienced entrepreneur, or anyone who regularly works with Microsoft Word, Excel, PowerPoint, and Office 365, this Microsoft Office skills course will provide you with a solid foundation and advanced techniques to maximise your productivity and efficiency. No prior experience is required, making it suitable for beginners and intermediate users looking to expand their knowledge and capabilities in the Microsoft Office suite. On the other hand, anyone who wants to establish their career as: like MS Office User Microsoft Office 2019 User Touch Typing Worker Audio Typist Can take this Ultimate Microsoft Office Skills Training (Word, Excel, PowerPoint, and 365) course. Requirements There is no prerequisite to enrol in this course. You don't need any educational qualification or experience to enrol in the Mastering Microsoft Office: Word, Excel, PowerPoint, and 365 course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online course. Career path Administrative Assistant - £20K to £30K/year Data Analyst - £25K to £45K/year Office Manager - £25K to £40K/year Project Coordinator - £25K to £35K/year Marketing Assistant - £20K to £30K/year Course Curriculum Section 01: Getting Started Introduction 00:03:00 Getting started on Windows, macOS, and Linux 00:01:00 How to ask great questions 00:01:00 FAQ's 00:01:00 Section 02: Excel 2021: Basics Excel Overview 00:05:00 Start Excel Spreadsheet 00:04:00 Enter Text and Numbers 00:07:00 Relative References 00:04:00 Working with ranges 00:07:00 Save and Save as Actions 00:08:00 File Extensions, Share, Export, and Publish files 00:06:00 Section 03: Excel 2021: Rows, Columns, and Cells Adding Rows and Columns 00:03:00 Modifying Rows and Column lengths 00:05:00 Section 04: Excel 2021: Data Handling Copy, Cut, and Paste 00:07:00 Copying Formulas 00:03:00 Section 05: Excel 2021: Page Setting Up and Print Page setup options 00:06:00 Fit to print on One Page 00:03:00 Print Workbooks 00:03:00 Section 06: Excel 2021: Sorting and Filtering Sorting Data Ascending Order 00:04:00 Sorting Data Descending Order 00:02:00 Filter Data 00:04:00 Section 07: Excel 2021: Writing Formulas Creating Basic Formulas 00:06:00 Datetime Formulas 00:06:00 Mathematical formulas phase1 00:20:00 Mathematical formulas phase2 00:12:00 Section 08: Excel 2021: Advanced Formulas VLOOKUP formula 00:12:00 HLOOKUP formula 00:04:00 Section 09: Excel 2021: XLOOKUP only for 2021 and Office 365 XLOOKUP 00:08:00 Handling #NA and Approximates match in XLOOKUP 00:11:00 Section 10: Excel 2021: Data and Tools Split Text into columns 00:07:00 Flash Fill 00:07:00 Data Validation 00:07:00 Remove Duplicates 00:08:00 Import Data from Text files 00:06:00 Import Data from .CSV files 00:03:00 Section 11: Excel 2021: Formatting data and tables Formatting Font 00:04:00 Formatting Alignment 00:06:00 Formatting Numbers 00:05:00 Formatting Date 00:03:00 Formatting Tables 00:05:00 Section 12: Excel 2021: Pivot Tables Pivot Tables 00:07:00 Pivot Charts 00:02:00 Section 13: Excel 2021: Charts Excel Charts - Categories 00:03:00 Elements of a chart 00:04:00 Creating Charts 00:02:00 Column or Bar charts 00:04:00 Formatting charts 00:04:00 Line Charts 00:02:00 Pie and Doughnut charts 00:04:00 Section 14: PowerPoint 2021: Course Introduction Overview 00:04:00 Start PowerPoint Presentation 00:05:00 Screen setting and Views 00:05:00 Section 15: PowerPoint 2021: Basics Presentation Tips and Guidelines 00:06:00 Creating a New Presentation 00:04:00 Working with Slides 00:04:00 Save a Presentation 00:04:00 Print Slides 00:03:00 Section 16: PowerPoint 2021: Text and Bullet Options Formatting Text 00:05:00 Slide Text Alignments 00:03:00 Multi-Column Text Alignments 00:02:00 Adding Bullets and Numbered List Items 00:03:00 Section 17: PowerPoint 2021: Adding Graphic Assets Insert Shapes 00:03:00 Insert Icons 00:03:00 Insert Graphics 00:04:00 Add 3D Models 00:03:00 Insert Pictures 00:03:00 Section 18: PowerPoint 2021: Picture Formatting Picture Options 00:04:00 Picture Cropping 00:03:00 Applying Built-in Picture Styles 00:04:00 Section 19: PowerPoint 2021: SmartArt Graphics Add SmartArt Graphic 00:03:00 Modifying SmartArt 00:03:00 Creating a Target Chart using SmartArt 00:03:00 Section 20: PowerPoint 2021: Working with Tables Create a Table on Slide 00:04:00 Formatting Tables 00:02:00 Inserting Tables 00:02:00 Table Layouts 00:01:00 Section 21: PowerPoint 2021: Working with Charts Add a Chart 00:02:00 Formatting Charts 00:02:00 Insert Chart from Microsoft Excel 00:03:00 Section 22: PowerPoint 2021: Adding Multimedia Adding Video to a Presentation 00:03:00 Adding Audio to a Presentation 00:02:00 Screen Recording and Adding 00:02:00 Section 23: PowerPoint 2021: Working with Transition Applying Transitions to Presentation 00:04:00 Section 24: PowerPoint 2021: Animation Object Animation 00:03:00 Effect Options 00:02:00 Advanced Animation 00:02:00 Triggers to control animation 00:02:00 Section 25: PowerPoint 2021: Slideshow Effects Onscreen Presentation 00:02:00 Hiding Slides 00:02:00 Changing Order of Slides 00:02:00 Copying Slides 00:02:00 Section 26: Word 2021: Introduction Overview of MS Word 00:04:00 Start MS Word 2021 00:05:00 Section 27: Word 2021: Basics Create a new blank document 00:04:00 Creating a paragraph text 00:05:00 Non-printing characters 00:03:00 Save a document 00:03:00 Open a document 00:01:00 Find and replace 00:04:00 Section 28: Word 2021: Word Formatting AutoCorrect options 00:03:00 Formatting text 00:04:00 Copy cut and paste 00:04:00 Character formatting 00:02:00 Format painter 00:04:00 Work with numbers 00:02:00 Add bullets 00:03:00 Outline creation 00:04:00 Section 29: Word 2021: Tables Creating a table 00:03:00 Adding rows and columns to a table 00:02:00 Formatting table data 00:02:00 Borders and shading 00:02:00 Sorting in a table 00:04:00 Draw a table 00:04:00 Convert text to table 00:03:00 Convert table to text 00:02:00 Insert a spreadsheet 00:02:00 Quick tables - readily available formats 00:02:00 Section 30: Word 2021: Styles Working with styles 00:02:00 Creating styles 00:02:00 Clear formatting 00:01:00 Section 31: Word 2021: Page Layout Margins 00:02:00 Orientation 00:01:00 Page size setting 00:01:00 Adding columns 00:03:00 Page break - section break 00:02:00 Adding watermark 00:03:00 Headers and footers 00:03:00 Section 32: Word 2021: Envelops and Lables Create envelops 00:02:00 Creating labels 00:02:00 Section 33: Word 2021: Mail Merges Creating a mail merge document 00:03:00 Section 34: Word 2021: Review and Printing Thesaurus and spell check 00:01:00 Word count 00:01:00 Speech - read aloud 00:01:00 Language - translate 00:01:00 Tracking 00:01:00

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