- Be proficient in data analytics tool and skill
- Career change to data analyst
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Data tools:
- Python(jupyter notebook)
- Excel, PowerBI
- SQL
- API integration
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Visulizatio & data storytelling
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Metholdology
- Statistics
- AB testing
- AARRR funnel
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Engineering (extra)
- Cloud:EC2
- Pipline tool: DBT, Airflow
Dataquest is a data science bootcamp that offers career path courses, skill paths courses, and free introductory courses.
- Text lecture: Reading is faster than watching video, contronl my own tempo
- Project-based: goal-oriented learning
- Real data: close to real world scenario
Data Analyst in Python - 99 Lessons · 20 Projects
| Outline | Section | Done |
|---|---|---|
| Part 1: Introduction to Python | Introduction to Python | x |
| For Loops and Conditional Statements in Python | x | |
| Dictionaries, Frequency Tables, and Functions in Python | x | |
| Python Functions and Learn Jupyter Notebook | x | |
| Python for Data Science: Intermediate | x | |
| Part 2: Intermediate Python and Pandas | Pandas and NumPy Fundamentals | x |
| Data Visualization Fundamentals | x | |
| Storytelling Data Visualization and Information Design | ||
| Part 3: Data Cleaning in Python | Data Cleaning and Analysis | |
| Data Cleaning in Python: Advanced | ||
| Data Cleaning Project Walkthrough | ||
| Part 4: The Command Line | Elements of the Command Line | |
| Text Processing in the Command Line | ||
| Part 5: Working with Data Sources | SQL Fundamentals | |
| Intermediate SQL for Data Analysis | ||
| APIs and Web Scraping in Python | x | |
| Data Analysis in Business | ||
| Part 6: Probability and Statistics | Statistics Fundamentals | |
| Intermediate Statistics: Averages and Variability | ||
| Probability: Fundamentals | ||
| Conditional Probability | ||
| Hypothesis Testing: Fundamentals | ||
| Part 7: Advanced Topics in Data Analysis | Command Line: Intermediate | |
| Git and Version Control | ||
| Part 8: Capstone Project | Data Analyst in Python Capstone Project | |