Skills for Today, Success for Tomorrow
This comprehensive course provides a practical introduction to Data Science and Machine Learning, guiding learners from foundational concepts to real-world applications. Students begin by exploring the scope, trends, and roles within data science, then build strong programming skills using Python, Jupyter, NumPy, Pandas, and Scikit-learn. The course emphasizes hands-on learning through data collection, cleaning, feature engineering, exploratory data analysis, and visualization. Learners progress to building and evaluating machine learning models for regression and classification, while also gaining exposure to big data concepts, cloud platforms, and tools like Google Colab and Kaggle. Alongside technical skills, the program develops professional competencies such as communication, freelancing basics, resume building, LinkedIn profiling, and interview preparation. The course concludes with a capstone project implementing an MNIST classification model, ensuring learners graduate with both practical experience and a portfolio-ready project.
