Course Description

In today’s data-driven world, organizations rely on data insights to make informed decisions and drive innovation. The Data Science and Machine Learning Training Program equips learners with essential skills in data analysis, statistics, and programming to build predictive models and solve real-world problems. The program covers Python for data analysis, data preprocessing, visualization, and exploratory data analysis (EDA) using NumPy, Pandas, Matplotlib, and Seaborn. Learners then explore supervised and unsupervised machine learning techniques such as regression, decision trees, clustering, SVMs, and neural networks. Advanced topics include deep learning, NLP, and model deployment using tools like Scikit-learn, TensorFlow, and Keras. Through hands-on projects and real-world case studies, participants gain practical experience in building, evaluating, and deploying machine learning models across various domains.

What will you learn in this Internship?

By the end of this internship, participants will be able to:

• Understand the core principles of data science and the machine learning workflow.
• Collect, clean, and analyze data using Python and popular data libraries.
• Apply key statistical and ML algorithms to build predictive and classification models.
• Evaluate model performance and optimize results using appropriate metrics.
• Visualize and communicate insights through dashboards and reports.
• Deploy machine learning solutions for real-world applications.