Published 1/2024
Created by Md Shahriar
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 80 Lectures ( 9h 21m ) | Size: 3.51 GB
Master Complete Data Analysis Workflow. Unleash Two Widely Used Tools – Excel and Python. Empower Yourself with ChatGPT.
What you’ll learn:
Learn Python’s syntax, data types, variables, and operators to construct simple programs and execute basic functions.
To manage program flow, use loops and conditional statements like if, elif, and else.
Learn to use Python lists, dictionaries, tuples, and sets.
Learn to access, change, and manipulate these structures for various programming needs.
Understand and apply techniques for cleaning and preparing raw data in Excel.
Learn to identify and handle missing data, outliers, and inconsistencies.
Utilize Excel functions and tools for data validation and transformation.
Explore fundamental statistical concepts and their application in Excel.
Learn to perform descriptive statistics, inferential statistics, and hypothesis testing using Excel functions and tools.
Understand how to interpret and communicate statistical results effectively.
Design and build interactive dashboards in Excel for effective data visualization.
Learn to use PivotTables, PivotCharts, and slicers to create dynamic and user-friendly dashboards.
Explore various data visualization techniques available in Excel, including charts, graphs.
Learn and apply the data analysis methodology, from data cleaning to hypothesis testing, in real-world applications.
Increase your critical thinking and problem-solving skills for data analysis, decision-making, and recommendation.
Use value counts, percentage, group by, pivot tables, correlation, and regression professionally and realistically.
Solve over 60+ real-world data analytical questions to practice applying data analysis to various circumstances.
Emphasize practical application to gain valuable insights from data and create educated judgments and suggestions.
Requirements:
Microsoft Excel
No coding Experience is Needed
Desire to learn
Description:
Chapter 1: IntroductionWelcome to the comprehensive and dynamic course, “Data Analysis 3 in 1: Excel, Python, and ChatGPT.” This meticulously crafted program is designed to empower learners with a versatile skill set, encompassing the efficient data manipulation capabilities of Excel, the scalability and coding flexibility of Python, and the intuitive coding assistance from ChatGPT. As technology continues to evolve, proficiency in multiple tools becomes essential. This course aims to provide a holistic understanding of the data analysis workflow, ensuring that learners can seamlessly transition from Excel to Python, while also adding a touch of AI for an enhanced coding experience.Chapter 2: Excel MasteryThe course kicks off with a deep dive into Excel, teaching you to wield its powerful features for data cleaning, transformation, and visualization. From managing missing data and outliers to leveraging advanced Excel functions and tools for statistical analysis, you’ll gain a solid foundation in Excel’s capabilities. The focus on interactive dashboard creation using PivotTables, PivotCharts, and various visualization techniques will empower you to present insights in a compelling and user-friendly manner.Chapter 3: Python Basics and BeyondBuilding on your Excel skills, the course introduces Python programming basics. You’ll learn the syntax, data types, and control structures, enabling you to construct simple programs. The emphasis is on practical application – generating, copying/pasting, adjusting, and running code with ease. Python’s ability to handle large datasets becomes evident, making it the tool of choice for scenarios where Excel’s limitations are surpassed. This section ensures you’re proficient in both tools, providing adaptability in real-world data analysis scenarios.Chapter 4: Statistical Analysis and InterpretationAs the course progresses, you’ll delve into fundamental statistical concepts, applying them using both Excel and Python. Descriptive statistics, inferential statistics, and hypothesis testing are covered comprehensively. You’ll learn not just how to perform these analyses but, crucially, how to interpret and communicate the results effectively. This knowledge forms the backbone of making informed decisions and recommendations based on data-driven insights.Chapter 5: Real-world Application and Problem-solvingThe final section of the course is dedicated to real-world application. You’ll tackle over 60+ data analytical questions, honing your skills in solving practical problems. Value counts, percentage calculations, grouping data, and utilizing advanced statistical techniques become second nature. Emphasis is placed on critical thinking and problem-solving, ensuring that you not only understand the tools and techniques but can confidently apply them to various circumstances. By the course’s conclusion, you’ll be equipped to navigate the complete data analysis workflow with mastery and confidence.
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