Python AI/ML & Data Science Course
Learn Python, Machine Learning, AI, and Data Science with real datasets and practical projects. Build ML models, analyze data, and gain job-ready skills with expert training.
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Course Content
7 Modules | 2 month
Module 1: Python Programming Foundations
- Python's Paradigm Shift
- The Data Structure Nexus
- Function Dynamics & Modular Architecture
- Control Flow Mechanisms
Module 2: Data Science with Python
- Cracking the Data Code
- Visualizing the Invisible
- Exploratory Data Analysis (EDA)
- Statistical Foundations
- From Data to Decisions
Module 3: Statitics & Probability for Machine Learning
- The Statistical Engine: Driving Insights in Machine Learning
- The Probability Playground
- Hypothesis Testing
- Correlation & Causation
- Statistical Sampling
- The Backbone of AI
Module 4: Machine Learning Foundations
- Supervised Learning Algorithms
- Evaluation Methodologies in Machine Learning
- Feature Engineering & Selection
- Overfittign & Underfitting
- Real-World Applications of Machine Learning
Module 5: Advanced Machine Learning & Unsupervised Learning
- Clustering Revelation
- Dimensionality Reduction
- Advanced Supervised Learning Algorithms
- Anomaly detection
- Ensemble Methods
Module 6: Deep Learning & Natural Language Processing (NLP)
- Deep learning Architectures
- Natural Language Processing
- Convolution neural Networks (CNNs)
- Recurrent Neural Networks (RNNs)
- Transformers & Attention Mechanisms
Module 7: Reinforcement Learning & AI Concepts
- Reinforcement Learning Paradigms
- The Core Principles of AI
- Markov Decision Processes
- Exploration Vs. Exploitation
- Ethics in AI