This document outlines a comprehensive day-by-day learning plan from April 16, 2024, to July 16, 2024. The plan is designed to provide a structured approach to mastering Python, Excel, and SQL in the first half, followed by Regression Analysis and Power BI in the second half. This schedule includes daily goals, with flexibility for adjustments based on learning pace and interests. Regular review days are integrated to consolidate knowledge, and community engagement is encouraged to enhance learning through discussion and practice.
Here is the revised schedule to match the dates starting from April 16, 2024 to July 16, 2024:
| Day | Date | Focus | Daily Goals & Resources |
|---|---|---|---|
| 1 | Apr 16, Tue | Python Basics | Start "Python for Everybody: Getting Started with Python" - Chapter 1 |
| 2 | Apr 17, Wed | Python Basics | Python for Everybody - Chapter 2: Variables and Expressions |
| 3 | Apr 18, Thu | Python Basics | Python for Everybody - Chapter 3: Conditional code |
| 4 | Apr 19, Fri | Python Basics | Python for Everybody - Chapter 4: Functions |
| 5 | Apr 20, Sat | Python Basics | Python for Everybody - Chapter 5: Loops and Iteration |
| 6 | Apr 21, Sun | Excel Basics | LinkedIn Learning: Excel Essential Training - Introduction |
| 7 | Apr 22, Mon | Excel Basics | Excel Essential Training - Basic Formulas and Calculations |
| 8 | Apr 23, Tue | SQL Basics | SQLZoo: Introduction to SQL - Basic SELECT Queries |
| 9 | Apr 24, Wed | SQL Basics | SQLZoo: Basic SELECT Queries - Continue practicing |
| 10 | Apr 25, Thu | Integration Day | Review Python Chapters 1-5; Apply Python to simple Excel tasks via openpyxl |
| 11 | Apr 26, Fri | Excel Intermediate | Excel Essential Training - Working with Sheets, Conditional Formatting |
| 12 | Apr 27, Sat | Excel Intermediate | Excel Essential Training - Data Functions and Tables |
| 13 | Apr 28, Sun | SQL Intermediate | SQLZoo: More SELECT Queries, Start using JOINs |
| 14 | Apr 29, Mon | SQL Intermediate | SQLZoo: Practice JOINs and Complex Queries |
| 15 | Apr 30, Tue | Python File Handling | Automate the Boring Stuff with Python - Chapter 8: Reading and Writing Files |
| 16 | May 01, Wed | Python Data Manipulation | Automate the Boring Stuff with Python - Chapter 12: Working with Excel Spreadsheets |
| 17 | May 02, Thu | Python and SQL | Learn Python by building a small app to query SQL databases using SQLAlchemy |
| 18 | May 03, Fri | Project Integration | Use Python to extract data from SQL, manipulate in Python, output to Excel |
| 19 | May 04, Sat | Project Integration Review | Debug and optimize yesterday's project |
| 20 | May 05, Sun | Excel Advanced | Excel Essential Training - Advanced Charting Techniques |
| 21 | May 06, Mon | SQL Advanced | SQLZoo: Subqueries and Advanced Data Manipulation |
| 22 | May 07, Tue | Rest and Reflect | Review all notes and exercises, rest, and prepare for the next week |
| 23 | May 08, Wed | Python: Working with APIs | Python for Everybody - Using Python to Access Web Data |
| 24 | May 09, Thu | Python: Data Visualization | Python for Everybody - Visualizing Data using Python |
| 25 | May 10, Fri | Excel: Data Analysis | Excel: Mastering Data Analysis - Introduce to Pivot Tables |
| 26 | May 11, Sat | Excel: Data Analysis | Continue with Pivot Tables and introduce Slicers and Timelines |
| 27 | May 12, Sun | SQL: Transaction and Security | SQLZoo: Learning Transactions and Database Security |
| 28 | May 13, Mon | SQL: Performance Tuning | SQLZoo: Indexes and Optimization Techniques |
| 29 | May 14, Tue | Python & SQL Integration | Build a complex data dashboard using Python and SQL |
| 30 | May 15, Wed | Python & Excel Integration | Automate a multi-step data workflow integrating Python and Excel |
| 31 | May 16, Thu | Python: Advanced Data Handling | Deep dive into pandas for data manipulation in Python |
| 32 | May 17, Fri | Python: Data Cleaning | Learn techniques for cleaning data using pandas |
| 33 | May 18, Sat | Excel: Advanced Formulas | Explore advanced formulas and array functions in Excel |
| 34 | May 19, Sun | Excel: Macros and Automation | Learn to record and write basic macros in Excel |
| 35 | May 20, Mon | SQL: Advanced Queries | Master complex SQL queries and views |
| 36 | May 21, Tue | SQL: Reports and Visualization | Learn to create reports and basic visualizations with SQL data |
| 37 | May 22, Wed | Rest and Reflect | Review all notes and exercises, rest, and prepare for the next phase |
| 38 | May 23, Thu | Python & SQL: Database Integration | Integrate Python with SQL for database operations and management |
| 39 | May 24, Fri | Python & Excel: Automation Scripts | Develop automation scripts in Python that use Excel as a data source |
| 40 | May 25, Sat | Project Day: Mini Project | Combine Python, SQL, and Excel skills in a mini project to automate monthly reports |
| 41 | May 26, Sun | Introduction to Regression Analysis | Start learning the basics of regression analysis |
| 42 | May 27, Mon | Regression Analysis: Simple Linear | Understand and implement simple linear regression models |
| 43 | May 28, Tue | Regression Analysis: Data Preparation | Prepare datasets for regression analysis |
| 44 | May 29, Wed | Regression Analysis: Multiple Linear | Study multiple linear regression techniques |
| 45 | May 30, Thu | Regression in Python | Use Python libraries (e.g., statsmodels, scikit-learn) for regression analysis |
| 46 | May 31, Fri | Introduction to Power BI | Begin learning Power BI, starting with the basics of dashboard creation |
| 47 | Jun 01, Sat | Power BI: Data Importing | Learn how to import and shape data in Power BI |
| 48 | Jun 02, Sun | Power BI: Visualizations | Explore creating various visualizations in Power BI |
| 49 | Jun 03, Mon | Power BI: DAX Basics | Introduction to DAX formulas in Power BI |
| 50 | Jun 04, Tue | Power BI: Intermediate DAX | Continue learning DAX with more complex examples |
| 51 | Jun 05, Wed | Rest and Reflect | Reflect on the week’s learning and prep for advanced DAX and data modeling |
| 52 | Jun 06, Thu | Power BI: Advanced DAX | Advanced DAX techniques for business solutions |
| 53 | Jun 07, Fri | Power BI: Data Modeling | Learn about data modeling and relationships in Power BI |
| 54 | Jun 08, Sat | Power BI: Publishing and Sharing | Explore how to publish and share Power BI reports and dashboards |
| 55 | Jun 09, Sun | Regression Analysis: Using Power BI | Apply regression analysis results in Power BI to create impactful visualizations |
| 56 | Jun 10, Mon | Comprehensive Project Planning | Plan a comprehensive project integrating all skills learned: Python, SQL, Excel, Power BI |
| 57 | Jun 11, Tue | Project Development: Data Collection | Start the comprehensive project by collecting and preparing data |
| 58 | Jun 12, Wed | Project Development: Data Analysis | Analyze the collected data using Python and SQL |
| 59 | Jun 13, Thu | Project Development: Regression Analysis | Implement regression analysis on the project data |
| 60 | Jun 14, Fri | Project Development: Visualization | Develop initial visualizations for the project data in Power BI |
| 61 | Jun 15, Sat | Project Development: Advanced Features | Integrate advanced DAX features in Power BI for the project |
| 62 | Jun 16, Sun | Project Development: Dashboard Completion | Complete the main dashboard for the project in Power BI |
| 63 | Jun 17, Mon | Project Review and Debugging | Review all elements of the project, debug any issues, optimize performance |
| 64 | Jun 18, Tue | Regression Analysis: Validation | Validate regression models, adjust parameters as necessary |
| 65 | Jun 19, Wed | Documentation Day | Document all processes and findings, prepare a presentation of the project |
| 66 | Jun 20, Thu | Presentation Preparation | Create slides and visuals for the project presentation |
| 67 | Jun 21, Fri | Dry Run Presentation | Conduct a dry run of the presentation to iron out any issues |
| 68 | Jun 22, Sat | Final Presentation | Present the comprehensive project to peers or mentors for feedback |
| 69 | Jun 23, Sun | Feedback Implementation | Implement feedback received from the presentation, refine project |
| 70 | Jun 24, Mon | Advanced Power BI: Real-time Data | Learn about and implement real-time data processing in Power BI |
| 71 | Jun 25, Tue | Advanced Power BI: API Integration | Integrate external APIs to pull data directly into Power BI dashboards |
| 72 | Jun 26, Wed | Rest and Reflect | Take a day off to rest, reflect on the learning progress and prepare for the final push |
| 73 | Jun 27, Thu | Power BI: Mobile Dashboard Design | Design and optimize dashboards for mobile viewing in Power BI |
| 74 | Jun 28, Fri | Power BI: Security Features | Explore security settings and report sharing in Power BI |
| 75 | Jun 29, Sat | Portfolio Preparation: Python and SQL | Start compiling Python and SQL projects for portfolio inclusion |
| 76 | Jun 30, Sun | Portfolio Preparation: Excel and Power BI | Include Excel and Power BI dashboards in the portfolio |
| 77 | Jul 01, Mon | Portfolio Review and Edit | Review the entire portfolio, edit for coherence and completeness |
| 78 | Jul 02, Tue | Mock Interviews | Conduct mock interviews using the portfolio as a showcase of your skills |
| 79 | Jul 03, Wed | Final Edits and Polishing | Make final edits to the portfolio, polish for presentation |
| 80 | Jul 04, Thu | Portfolio Presentation Rehearsal | Rehearse presenting your portfolio |
| 81 | Jul 05, Fri | Advanced SQL: Performance Tuning | Dive deeper into SQL performance tuning to optimize database queries |
| 82 | Jul 06, Sat | Advanced SQL: Automated Reporting | Automate SQL reporting processes |
| 83 | Jul 07, Sun | Advanced Python: Machine Learning Basics | Learn basic machine learning concepts applicable in Python |
| 84 | Jul 08, Mon | Advanced Python: Machine Learning Application | Apply machine learning techniques to a dataset |
| 85 | Jul 09, Tue | Python and Power BI Integration | Create a data pipeline from Python to Power BI for automated dashboard updates |
| 86 | Jul 10, Wed | Project Finalization | Finalize any remaining project components, ensure all integrations are functioning |
| 87 | Jul 11, Thu | Career Planning | Map out potential career paths, identify companies and roles of interest |
| 88 | Jul 12, Fri | Job Application Process | Prepare resumes and cover letters, set up LinkedIn and other professional profiles |
| 89 | Jul 13, Sat | Networking and Outreach | Reach out to professionals in the field, attend webinars or local meetups |
| 90 | Jul 14, Sun | Final Project: Regression Analysis | Develop a comprehensive regression model using historical data and analyze results |
| 91 | Jul 15, Mon | Final Project: Power BI Dashboard | Construct a dynamic Power BI dashboard to visualize regression outputs |
| 92 | Jul 16, Tue | Portfolio Compilation | Compile all projects, scripts, and dashboards into a cohesive portfolio; Reflect on learnings |
This detailed schedule is structured to ensure deep and systematic understanding of Python, Excel, SQL, Regression Analysis, and Power BI. By dedicating focused time each day to these topics, I aim to build a strong foundation in data analysis and visualization techniques, preparing for advanced studies or professional challenges.