A Data Science course provides students with the knowledge and skills to analyze, interpret, and manage large datasets to solve real-world problems. The course typically covers a broad range of topics, including statistics, machine learning, data visualization, data wrangling, and programming. Students learn to use tools like Python, R, SQL, and platforms like Jupyter Notebooks to analyze and model data.
Key concepts include data cleaning, feature engineering, exploratory data analysis (EDA), and the application of machine learning algorithms such as regression, classification, clustering, and decision trees. The course also emphasizes the importance of understanding the underlying statistical principles to make data-driven decisions and create predictive models.
Additionally, students are introduced to big data technologies like Hadoop and Spark for handling large datasets, as well as libraries such as TensorFlow and PyTorch for deep learning. Visualization tools like Matplotl