• Focus on Excel as a crucial tool for data analysis
• Learn the importance and practical uses of Excel
• Explore workbook creation
• Understand common Excel functions
• Study conditional aggregation
• Discover pivot tables and charts
• Examine slicers and time slicers
• Build a strong foundation for the remainder of the course

• Learn to apply conditional formatting in Excel
• Discover how to import data effectively
• Understand the process of adding to data models
• Master pivoting using multiple tables
• Gain expertise in Excel's PowerQuery and PowerPivot
• Dive into Data Analysis Expressions (DAX)
• Explore creating measures and KPIs
• Perform what-if analysis in Excel
• Get acquainted with the data analysis tool package
• Participate in cohort quizzes, assignments, and exercises to reinforce learning

• Understand the anatomy of an SQL query
• Learn about Common Table Expressions in SQL
• Explore generating data and creating a Date Dimension
• Dive into random data generation and sampling techniques
• Grasp train/test split implementation with SQL
• Test your knowledge with a Basic SQL for Data Analysis quiz
• Delve into describing a series in descriptive statistics
• Discover how to describe a categorical series
• Assess your understanding with a Descriptive Statistics quiz

• Master the concept of grouping in SQL
• Learn about conditional aggregates and subtotals
• Evaluate your understanding with a Grouping and Subtotals quiz
• Discover aggregate expressions in SQL
• Understand window frames and their application
• Explore accessing next and previous rows in SQL
• Dive into SQL ranking functions
• Test your knowledge with a Running and Cumulative Aggregation quiz

• Learn to compare missing values in Interpolation
• Explore back filling and forward filling techniques
• Understand linear interpolation
• Test your knowledge with an Interpolation quiz
• Discover the concept of binning in data analysis
• Learn about equal-height binning
• Dive into equal-width binning
• Assess your understanding with a Binning quiz

• Discover what PowerBI is and its purpose
• Learn data visualization best practices
• Understand the high-level overview and components of PowerBI
• Gain experience in importing data and creating visuals

• Master data transformation techniques in PowerBI
• Learn how to create relationships between data sets
• Engage with cohort quizzes, assignments, and exercises to reinforce learning

• Learn how to publish reports in PowerBI
• Discover how to create engaging dashboards
• Dive into real-time visuals for dynamic data representation
• Explore custom visuals for tailored visualizations
• Understand security and sharing practices in PowerBI
• Maximize usage and efficiency of PowerBI tools
• Enhance learning through cohort quizzes, assignments, and exercises

• Get started with Python for analytics
• Understand essential data structures in Python
• Learn about control flow and built-in functions
• Explore Numpy, an external library for numerical computing
• Discover Scipy, an external library for scientific computing
• Practice using Numpy and Scipy through exercises
• Review solutions for Numpy and Scipy exercises
• Work with comma-separated files (CSV)
• Learn how to handle JSON files
• Manage raw files in Python
• Exercise: Read and analyze the Auto MPG dataset
• Review solutions for reading the Auto MPG dataset

Describing Data:

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• Learn about statistics and counts in data analysis
• Understand reshaping the data
• Practice group-by aggregations through exercises
• Review solutions for group-by aggregations exercises

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Cleaning Data:

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• Explore how to handle missing data
• Learn to identify and manage outliers
• Understand the importance of scaling data
• Dive into working with categorical data
• Exercise: Clean the Auto MPG dataset
• Review solutions for cleaning the Auto MPG dataset

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Visualizing Data:

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• Get introduced to data visualization techniques
• Learn to create scatter plots for data representation
• Understand and create bar plots for data visualization
• Explore visualizing data distributions
• Learn to represent data using line graphs
• Discover the use of heat maps in data visualization
• Master the art of multi-plot grids for data representation
• Exercise: Visualize the Auto MPG dataset
• Review solutions for visualizing the Auto MPG dataset
• Test your understanding with self-assessment questions

Final Project Options:

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• Create a Sales Analysis Dashboard using Excel or Power BI
• Perform Social Media Analytics with Power BI

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Career Preparation:

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• Get assistance with resume review and creation
• Participate in a mockup interview to prepare for real interviews
• Learn to create an effective LinkedIn profile for job search