AI & DATA SCIENCE
Course Outcomes
Master machine learning algorithms including supervised, unsupervised, and reinforcement learning.
Develop proficiency in Python programming and essential data science libraries like NumPy, Pandas, and Scikit-learn.
Build and deploy neural networks using deep learning frameworks such as TensorFlow and PyTorch.
Apply statistical analysis and hypothesis testing to validate data-driven conclusions.
Create compelling data visualizations and interactive dashboards using tools like Matplotlib, Seaborn, and Plotly.
Implement natural language processing techniques for text analysis and sentiment analysis.
Design and optimize recommendation systems and predictive models for business applications.
Evaluate model performance using cross-validation, metrics, and ethical AI practices.









