Python for Data Science – Study Plan
Here’s a suggested study plan to learn Python for data science with resources and timeline: Week 1: Python Basics Learn basic Python syntax, data types, and control structures Learn how to work with strings, lists, and dictionaries Familiarize yourself with functions and modules in Python Resources: Codecademy’s Python 3 Course (free) Python for Data Analysis by Wes McKinney (book) Week 2-3: Numpy and Pandas Learn how to use NumPy for numerical computing in Python Learn how to use Pandas for data manipulation and analysis Practice with sample datasets and perform basic operations on them Resources: NumPy Tutorial by DataCamp (free) Pandas Tutorial by DataCamp (free) Python for Data Analysis by Wes McKinney (book) Week 4-5: Data Visualization with Matplotlib and Seaborn Learn how to use Matplotlib and Seaborn for creating visualizations in Python Practice creating different types of charts and graphs Resources: Matplotlib Tutorial by DataCamp (free) Seaborn Tutorial by DataCamp (free) Python for Data Analysis by Wes McKinney (book) Week 6-7: Machine Learning with Scikit-Learn Learn how to use Scikit-Learn for machine learning in Python Practice with sample datasets and perform basic operations on them Learn about popular algorithms like linear regression, logistic regression, and k-nearest neighbors Resources: Scikit-Learn Tutorial by DataCamp (free) “Hands-On Machine Learning with Scikit-Learn and TensorFlow” by Aurélien Géron (book) Week 8-9: Deep Learning with TensorFlow and Keras Learn how to use TensorFlow and Keras for deep learning in Python Practice with sample datasets and perform basic operations on them Learn about popular deep learning architectures like convolutional neural networks and recurrent neural networks Resources: TensorFlow Tutorial by DataCamp (free) Keras Tutorial by DataCamp (free) “Deep Learning with Python” by François Chollet (book) Week 10: Capstone Project Apply your skills by working on a capstone project Use real-world data to perform analysis, visualization, and/or machine learning tasks Showcase your work by creating a report or presentation Resources: Kaggle Datasets (free) UCI Machine Learning Repository (free) GitHub (for hosting and sharing your project) Of course, this timeline is just a suggestion and can be adjusted based on your schedule and pace of learning. The resources mentioned are just a starting point and there are many other free and paid resources available online for learning Python and data science. Good luck!