Multi-Cloud AI/ML Technology – 6-Week Course  – Syllabus

Objective: Enable learners to develop, deploy, and manage AI/ML solutions across AWS, Azure, and GCP using best practices in Data Engineering, AI Model Deployment, and MLOps.

6-Week AI & ML Journey – From Basics to Mastery
Hands-on learning with real-world applications in AI and ML!

🔹 Week 1: AI/ML Fundamentals with Python
Course:

Python for Data Science and Machine Learning
📌 Keywords: Python, AI basics, Data Science, Hands-on coding, Real-world examples
💡 Overview:
Grasp the fundamentals of AI and its pervasive impact in today’s world.​
Develop proficiency in Python programming, the leading language for AI.​
Learn data analysis techniques that enable machines to make predictions.​
Explore the foundational concepts of machine learning algorithms.​

🔹 Week 2: Supervised Learning Techniques
Course:

Practical Machine Learning with Python
📌 Keywords: Supervised Learning, Regression, Classification, Model Evaluation
💡 Overview:
Understand supervised learning and its applications.​
Implement regression algorithms for predictive modeling.​
Explore classification techniques for categorizing data.​
Evaluate model performance using appropriate metrics.​

🔹 Week 3: Unsupervised Learning and Data Clustering
Course:

Unsupervised Learning with Python
📌 Keywords: Unsupervised Learning, Clustering, Pattern Recognition, Data Insights
💡 Overview:
Discover unsupervised learning methods for uncovering hidden patterns.​
Implement clustering algorithms such as K-Means.
Analyze large datasets to extract meaningful insights.​
Apply clustering techniques to real-world scenarios.
🔹 Week 4: Machine Learning Model Deployment
Course:

Deploying Machine Learning Models
📌 Keywords: Model Deployment, MLOps, Automation, Real-World Applications
💡 Overview:
Learn the principles of deploying machine learning models into production.​
Understand the MLOps pipeline and its components.
Automate data preprocessing, model training, and deployment tasks.​

🔹 Week 5: Natural Language Processing (NLP)
Course:

NLP Techniques and Applications
📌 Keywords: Natural Language Processing, Text Analysis, Sentiment Analysis, Chatbots
💡 Overview:
Train AI models to understand and process human language.​
Perform sentiment analysis to gauge public opinion.​
Develop AI-powered chatbots for automated communication.​
Explore real-world applications of NLP in various industries.​

🔹 Week 6: Advanced AI Techniques and Generative Models
Course:

Generative AI and Large Language Models
📌 Keywords: Generative AI, Large Language Models, Future of AI
💡 Overview:
Understand the development and applications of Large Language Models (LLMs).​
Build generative AI models from scratch using Python.
Discuss the future trends and ethical considerations in AI.​

Deliverables & Outcomes

Hands-on Multi-Cloud AI Projects
Deploying AI Models on AWS, Azure, GCP
Building an MLOps Pipeline
Final Capstone Project
Completion Certificate