Description
This course offers a comprehensive introduction to Python for data science, equipping participants with the skills to manipulate, analyze, and visualize data effectively. Starting with foundational Python programming, the course progresses to cover essential tools like Pandas for data manipulation, Matplotlib and Seaborn for visualization, and Numpy for numerical computations. Participants will learn to work with relational databases like SQLite and PostgreSQL, as well as NoSQL databases like MongoDB, to manage and analyze large datasets. The course also explores using Jupyter Notebooks for organizing analyses, cleaning and preparing data, and performing advanced computations with SciPy. By the end, attendees will be prepared to tackle real-world data challenges and make data-driven decisions confidently.
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