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Certificate in Data Science

This course offers an intensive, hands-on introduction to data science, guiding students through foundational Python programming, data wrangling, statistical analysis, and machine learning techniques over a 3-month period. Through practical exercises, real-world projects, and a capstone assignment, participants will develop the skills necessary to collect, clean, analyze, and model data, preparing them for advanced applications in data science.

What You Will Learn:

By the end of this course, participants will master Python for data science by understanding programming fundamentals (variables, data types, loops, and control flow), writing clean and efficient code to solve real-world data problems, performing data wrangling and exploration (collecting, cleaning, preprocessing datasets, and using libraries like Pandas and NumPy for analysis), conducting statistical analysis (descriptive and inferential statistics, probability distributions, and hypothesis testing), building and evaluating machine learning models (regression, classification, clustering, and performance evaluation using metrics like accuracy, precision, and recall), visualizing data effectively (using Matplotlib and Seaborn to create meaningful visualizations and craft compelling reports), and working on real-world data science projects, culminating in a capstone project to integrate and apply all learned skills.