Signature Program · P/01
Complete AI Practitioner Program
Machine Learning, Artificial Intelligence & Generative AI — from foundations to deployment.
A 10-week live AI training program for professionals and teams who want real, working AI capability. Go from Python and statistics through machine learning, deep learning, NLP and generative AI — and finish in ML Ops, deploying what you build.
- 10 Weeks
- 8 Modules
- Live · Online
- 6 Days / Week
- Individual + Corporate Teams
01 — Overview
Built for anyone serious about becoming AI-capable.
No prior AI experience required. The program starts at Python and statistics and carries you all the way to deploying Generative AI applications and ML pipelines in production.
Career-switchers & aspirants
Starting from a clean slate? This program is designed so foundations are never assumed — Python, statistics and data basics come first, on purpose.
Engineers, analysts & managers
Working professionals who want real, deployable AI capability — not just tool usage — and who need to keep pace with an AI-shifting industry.
Corporate cohorts
Organisations that need teams who can ship AI — the same program delivered for a company's own cohort, from foundations to ML Ops.
02 — The Journey
One week at a time. Zero to deploy.
Ten weeks are mapped into eight modules - each one building on the last, from your first line of Python to shipping a Generative AI application.
Python & Exploratory Data Analysis
- Foundation & programming skills
- Python for Data Science
- Data visualization in Python
- Exploratory Data Analysis (EDA)
Statistics
- Descriptive statistics
- Probability & distributions
- Inferential statistics
- Hypothesis testing
Machine Learning I
- Regression scenarios & advanced regression
- Naïve Bayes
- Model building & evaluation
- Tree models, Random Forests & boosting
Deep Learning
- Neural network fundamentals
- CNN architectures & transfer learning
- Recurrent Neural Networks
- Building with Python
Deep Learning + NLP
- RNN applications in language
- Lexical & syntactic processing
- Named Entity Recognition (NER) & CRF
NLP + Generative AI
- Semantic processing
- Topic modeling
- The shift from NLP into transformers
Generative AI
- Attention mechanism & transformers
- Generative AI, ChatGPT & prompt engineering
- Application deployment with Flask
- Multimodal LLMs
Generative AI + ML Ops
- Embedding & indexing large documents
- LangChain agents & tools
- Scaling & deploying Gen AI applications
- MLflow & deployment pipelines
03 — The Curriculum
Eight modules. Everything you need.
Each module ends with hands-on assignments — and the program carries you through industry projects and case studies.
Python & EDA
- Foundations & programming
- Python for Data Science
- Visualization
- Exploratory Data Analysis
Statistics
- Descriptive statistics
- Probability & distributions
- Inferential statistics
- Hypothesis testing
Machine Learning I
- Regression & Naïve Bayes
- Model building & evaluation
- Tree models & Random Forests
- Boosting & model selection
Machine Learning II
- Unsupervised learning
- Clustering techniques
- Pattern discovery in data
Deep Learning
- Neural network fundamentals
- CNNs & transfer learning
- RNNs with Python
Natural Language Processing
- Lexical, syntactic & semantic processing
- NER & Conditional Random Fields
- Topic modeling
Generative AI
- Transformers & attention
- Prompt engineering & ChatGPT
- LangChain agents & multimodal LLMs
- Deployment with Flask
ML Ops
- Business objectives
- Designing ML pipelines
- MLflow
- Deployment pipelines
04 — How You'll Learn
Theory that turns into working skill.
Every module includes hands-on assignments so you practise what you just learned before moving on.
Apply everything to real-world scenarios — the kind of problems you'll actually meet on the job.
Analyse industry use cases and learn how AI decisions are made in practice, not just in theory.
Interactive live Q&A and discussion — ask anything, get answers in the room.
05 — Format & Commitment
Structured for working professionals.
10 weeks
Live online program — six days a week, with a minimum of 1.5 hours per session.
Live & online
Instructor-led sessions with interactive Q&A — not recorded lectures. Ask questions, get answers in the room.
Hands-on throughout
Assignments after every module, industry projects and case studies woven through the arc, and real deployment at the end.
06 — Outcomes
What you'll be able to do at the end.
- Build, evaluate and select machine learning models end-to-end with Python.
- Engineer deep learning and NLP pipelines — from CNNs and RNNs to named-entity recognition and topic modeling.
- Build and deploy Generative AI applications — prompt engineering, LangChain agents, multimodal LLMs.
- Design ML Ops pipelines with MLflow and take models to production.
- Frame AI solutions around business objectives and defend them in interviews and to stakeholders.
Ready to become AI-capable?
One conversation. Real clarity. Book a free 1:1 strategy call — individual or corporate cohort.