Udemy – Fast-Track Data Analytics 3 in 1: Excel Python + ChatGPT 3.5 2024-1

Apr 18, 2025 - 19:54

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Fast-Track Data Analytics 3 in 1: Excel Python + ChatGPT 3.5. This course helps you improve your analytical skills by combining the capabilities of Excel, Python, and ChatGPT 3.5. First, you will be introduced to advanced Excel tools and learn how to clean, transform, and visualize data. Then, you will be introduced to the basics of Python programming and gain the ability to work with large datasets. Next, you will practice statistical concepts such as descriptive and inferential statistics using both tools. You will also learn how to code and analyze data more intelligently with the help of ChatGPT 3.5. By the end of the course, you will be able to analyze data and provide practical solutions by solving over 60 real-world problems. This course will prepare you to face real-world challenges and make data-driven decisions.

What you will learn:

Learn Python syntax, data types, variables, and operators to build simple programs and perform basic functions.
Use loops and conditional statements such as if, elif, and else to manage program flow.
Learn to use Python lists, dictionaries, tuples, and collections.
Learn how to access, modify, and manipulate these structures for various programming needs.
Understand and apply raw data cleaning and preparation techniques in Excel.
Learn how to identify and manage missing data, outliers, and inconsistencies.
Use Excel functions and tools to validate and transform data.
Review basic statistical concepts and their application in Excel.
Learn how to perform descriptive statistics, inferential statistics, and hypothesis testing using Excel functions and tools.
Understand how to effectively interpret and communicate statistical results.
Design and build interactive dashboards in Excel for effective data visualization.
Learn how to use PivotTables, PivotCharts, and slicers to create dynamic, user-friendly dashboards.
Explore the various data visualization techniques available in Excel, including charts and graphs.
Learn and apply data analysis methods, from data cleaning to hypothesis testing, in real-world applications.
Enhance critical thinking and problem-solving skills for data analysis, decision-making, and proposal making.
Professional and realistic use of counting values, percentages, grouping, pivot tables, correlations, and regression.
Solve over 60 real-world data analysis questions to practice applying data analysis in a variety of situations.
Emphasis on practical application to gain valuable insights from data and make informed judgments and recommendations.