Learning Python · Data Alchemy

Learning Python

Hi All,

I have worked as a BI Developer/data analysis for a few years now but only used SAS and Sql. I have picked up the basics of Python but want to learn more. So I asked ChatGPT to provide a study plan to learn Python for a data scientist. The following is what ChatGPT returned. I think it's a good start. For those of you that know Python, would you suggest something different?

Python Data Scientist Study Plan:

To embark on your journey to becoming a data scientist with a focus on Python, given your 10-hour weekly commitment and preference for video resources, here's a structured study plan:

### 12-Week Study Plan for Python Data Science

#### Weeks 1-3: Python Basics

- **Objective:** Learn Python fundamentals, including syntax, data types, and control structures.

- **Resources:**

- [Codecademy: Learn Python](https://www.codecademy.com/learn/learn-python-3) (3 hours/week)

- [YouTube: Corey Schafer's Python Beginner Tutorials](https://www.youtube.com/playlist?list=PL-osiE80TeTt2d9bfVyTiXJA-UTHn6WwU) (2 hours/week)

- **Practice:** Apply concepts on [HackerRank](https://www.hackerrank.com/domains/tutorials/10-days-of-python) (5 hours/week).

- **Weekly Goal:** Complete exercises and small coding challenges.

#### Weeks 4-6: Data Handling and Visualization

- **Objective:** Understand data manipulation with Pandas, NumPy, and introductory data visualization.

- **Resources:**

- [DataCamp: Pandas Fundamentals](https://www.datacamp.com/courses/pandas-foundations) (3 hours/week)

- [YouTube: Data School - Pandas](https://www.youtube.com/playlist?list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y) (3 hours/week)

- **Practice:** Analyze datasets from [Kaggle](https://www.kaggle.com/datasets) (4 hours/week).

- **Weekly Goal:** Perform basic data analysis and visualization on different datasets.

#### Weeks 7-9: Intermediate Python and Data Analysis

- **Objective:** Dive deeper into Python, focusing on data analysis libraries and techniques.

- **Resources:**

- [DataCamp: Intermediate Python for Data Science](https://www.datacamp.com/courses/intermediate-python-for-data-science) (3 hours/week)

- [YouTube: Sentdex - Python Data Analysis](https://www.youtube.com/playlist?list=PLQVvvaa0QuDfSNOGEf6hbMreVgKAC5MzG) (4 hours/week)

- **Practice:** Work on real-world data projects (3 hours/week).

- **Weekly Goal:** Build and document a mini-project using data analysis.

#### Weeks 10-12: Machine Learning Basics

- **Objective:** Introduction to machine learning concepts and techniques using Python.

- **Resources:**

- [Coursera: Machine Learning with Python](https://www.coursera.org/learn/machine-learning-with-python) (3 hours/week)

- [YouTube: Simplilearn - Machine Learning Basics](https://www.youtube.com/watch?v=7eh4d6sabA0) (3 hours/week)

- **Practice:** Implement basic machine learning models on datasets (4 hours/week).

- **Weekly Goal:** Create simple machine learning models and understand their applications.

### Additional Tips

- **Stay Consistent:** Regular, daily study is more effective than longer, less frequent sessions.

- **Join Communities:** Platforms like [Stack Overflow](https://stackoverflow.com/) and [Reddit's r/learnpython](https://www.reddit.com/r/learnpython/) can offer support and answer questions.

- **Review and Adjust:** Regularly assess your understanding and adjust the plan if necessary.

This plan is a starting point. The field of data science is vast, and continuous learning and application are key to success.

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