Machine Learning and AI with Python
Master core ML algorithms in Python and implement secure AI systems using semantic search, RAG, and LangChain.
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Audience: Data analysts, Software Engineers, Data Scientists
Duration: 3 days
Format: Lectures & hands‑on labs (50% lecture, 50% lab)
Overview
Machine Learning is transforming industries. This course introduces popular ML algorithms and demonstrates secure, responsible AI implementation—avoiding third‑party data exposure and maintaining control over training data.
Objective
Master core ML algorithms in Python and implement secure AI systems using semantic search, RAG, and LangChain.
What You Will Learn
- Python basics: Jupyter, NumPy, Pandas
- ML landscape and AI vocabulary
- Linear & Logistic Regression, Classification, Clustering
- Prompt engineering and semantic search
- LangChain workflows and cloud architecture best practices
Course Details
Audience: Data analysts, Software Engineers, Data Scientists
Duration: 3 days
Format: Lectures & hands‑on labs (50% lecture, 50% lab)
- Programming background
- Python familiarity helpful
Setup: Cloud‑based lab • Laptop • Chrome browser
Detailed Outline
- Intro to Python
- Jupyter notebooks
- NumPy & Pandas
- Labs
- ML landscape
- Deep‑Learning use cases
- AI/ML/DL definitions
- Data & AI
- Hardware & software ecosystem
- Types of ML
- Linear Regression
- Logistic Regression
- House price & other labs
- Iterative dev
- Summarizing
- Inferring
- Transforming
- Expanding
- Chatbot
- Labs
- Document chunking
- Vector DBs
- Hybrid search
- Anomaly detection
- Lab
- Models, prompts, parsers
- Memory
- Chains
- Q&A
- Evaluation
- Functions‑Tool‑Agents
- Lab
- Multi‑cloud overview
- Private data control
- Serverless LLM
- Database agents
- Customer service with AI
Ready to Get Started?
Contact us to learn more about this course and schedule your training.