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The Data Science course offers a complete introduction to the field of data analysis, machine learning, and predictive modeling. It covers essential concepts such as data collection, data cleaning, exploratory data analysis, statistical modeling, and data visualization using tools like Python, Pandas, NumPy, Matplotlib, and Seaborn.
Learners will also explore advanced topics such as machine learning algorithms, model evaluation, and deployment using popular libraries like Scikit-learn and TensorFlow. The course emphasizes practical, project-based learning, enabling students to work on real-world datasets to solve business problems and generate actionable insights.
By the end of the course, participants will possess the skills needed to pursue roles such as Data Scientist, Data Analyst, or Machine Learning Engineer. They will be equipped to handle data-driven decision-making tasks across industries like finance, healthcare, retail, and technology.