This course integrates data science methodologies with artificial intelligence to extract insights from structured and unstructured data. It covers end-to-end data pipelines, predictive modeling, and AI-driven analytics for decision-making in business, healthcare, and engineering domains.
Fundamental Topics
Fundamentals of AI and Data Science, covering Python, data preprocessing, EDA, statistics, machine learning, and databases.
Python for data science
Statistics & probability
Data preprocessing
Intermediate Topics
Intermediate AI and Data Science covering machine learning algorithms, feature engineering, model tuning, deep learning, NLP, and forecasting.
Machine learning algorithms
Feature engineering
Data visualization
Advanced Topics
Advanced AI and Data Science covering deep learning architectures, reinforcement learning, NLP, computer vision, big data, and AI deployment.
Deep learning
Big data analytics
AI-driven decision systems
Course Outcomes
Gain expertise in AI, machine learning, deep learning, data analysis, NLP, computer vision, and deployment.