environment, write basic Python scripts, experiment with input/output, and practice using conditional statements
- Study Hours: 10-12 hours
Week 2: Python Loops and Lists
- Topics: Loops (for, while, nested), Break and Continue, Problem-Solving with Loops, Introduction to Lists, Slicing, Iteration, Functions, List Comprehension
- Activities: Focus on iterative problem-solving, manipulate lists, practice list comprehension, and solve loop-related problems
- Study Hours: 10-12 hours
Week 3: Tuples, Dictionaries, and Sets
- Topics: Tuples (slicing, iteration, functions), Dictionaries (functions, nested dicts), Sets (methods, problem-solving)
- Activities: Learn to use different collection types in Python, solve problems using tuples, dictionaries, and sets, and practice using these structures in real-world applications
- Study Hours: 8-10 hours
Week 4: Python Functions and Modules
- Topics: Functions (parameters, arguments, recursion), Lambda functions, Local/Global variables, In-built and custom modules
- Activities: Write functions with varying complexity, use recursion, create and use custom modules, and explore built-in Python modules
- Study Hours: 10-12 hours
Month 2: Data Manipulation and Visualization
Week 5: Numpy for Data Manipulation
- Topics: Numpy arrays (creation, slicing), Mathematical operations, Sorting, Filtering, Aggregating, Statistical functions
- Activities: Perform data manipulation using Numpy, understand array manipulation, and apply mathematical operations on large datasets
- Study Hours: 12-14 hours
Week 6: Pandas for Data Analysis
- Topics: DataFrames, Handling missing data, GroupBy, Merging, Concatenation, Pivoting, Melting
- Activities: Work with Pandas DataFrames, clean and transform data, and perform analysis using real-world datasets
- Study Hours: 12-14 hours
Week 7: Matplotlib for Data Visualization
- Topics: Basic plotting (Bar, Line, Pie charts), Advanced plotting (Violin, Stem, Subplots), Seaborn project
- Activities: Create visualizations using Matplotlib, work on data visualization projects, and explore Seaborn for advanced plots
- Study Hours: 10-12 hours
Week 8: MySQL for Data Analytics
- Topics: MySQL basics, Importing data, Select queries, Aggregate functions, Joins, Subqueries, Views
- Activities: Set up MySQL, write complex queries, work with data in SQL, practice database operations, and extract meaningful insights from datasets
- Study Hours: 14-16 hours
Month 3: Excel, Power BI, and Final Projects
Week 9: Advanced MySQL
- Topics: Stored Procedures, Window Functions, Group By, Having clause, Complex subqueries
- Activities: Write advanced SQL queries, understand performance optimization, and practice complex data manipulation
- Study Hours: 12-14 hours
Week 10: Excel for Data Analytics
- Topics: Functions (COUNTIF, SUMIF, XLOOKUP), Power Query, Data Cleaning, Dashboard Creation
- Activities: Practice Excel data analysis, create automated reports, and design a dashboard using Excel
- Study Hours: 10-12 hours
Week 11: Power BI Essentials
- Topics: Power BI Installation, Data Modeling, DAX Functions, Visualizations, Publishing Reports
- Activities: Connect and transform data in Power BI, create reports, and explore DAX for custom calculations
- Study Hours: 12-14 hours
Week 12: Final Project and Review
- Activities: Work on a comprehensive project combining Python, MySQL, and Power BI, focusing on real-world data analytics
- Study Hours: 12-14 hours