This comprehensive course bridges the gap between data analytics and artificial intelligence, teaching you how to extract insights from data and build intelligent systems. You'll master essential tools like AI With Python, Pandas, NumPy, Scikit-learn, and TensorFlow while learning statistical methods and machine learning algorithms that power modern AI applications.

The curriculum covers the complete data science pipeline from data collection and cleaning to advanced analytics and predictive modeling. You'll work on real-world datasets, build machine learning models, and learn to interpret results for business decision making. Whether you're looking to start a career in data science or enhance your Analytics skills, this course provides the practical knowledge you need.

Key Topics Covered

• Data manipulation and visualization techniques
• Statistical Analytics and hypothesis testing
• Feature engineering and model evaluation
• Neural networks and deep learning basics
• Natural Language Processing (NLP) techniques
• Deploying models for production use