Get ready to build
Set up Python, Git and your development environment. Refresh Python and API fundamentals, and get ready for Live Labs.
A common technical starting point
Trycle in collaboration with IIIT Kottayam
Artificial Intelligence & Machine Learning Engineering
The IIIT Kottayam Artificial Intelligence and Machine Learning Program is a 7-month journey meant for graduates and final-year students who want to build competencies in machine learning and AI engineering.
- IIIT Kottayam academic certificates
- 12 credits across 4 courses
- Live Labs / industry internship
At a Glance
- Duration
- 7 months
- Mode
- Academics + Live Labs
- Academic hours
- 180 hours
- Live Industry Work
- 260 Hours
- Credential
- IIIT Kottayam + Industry Certificate
- Inaugural Cohort Price
- ₹90,000 + Taxes
- Eligibility
- 12th standard with Mathematics
- Credits
- 12 credits across 4 courses
Program Summary
The IIIT Kottayam Artificial Intelligence and Machine Learning program is a 7-month journey for learners who want to build competencies in machine learning and AI engineering.
The program comprises two parallel components: four self-paced academic courses delivered by IIIT Kottayam faculty and practical AI Engineering Live Labs. The Live Labs are a three-month working engagement at a partner AI company where students work on real projects with defined responsibilities as part of the company.
The program concludes with a structured career preparation phase covering portfolio documentation, CV and LinkedIn review, mock interviews, and access to career referrals.
Two parallel learning tracks
- Academic: four self-paced courses delivered by IIIT Kottayam faculty
- Practical: AI Engineering Live Labs with a partner AI company
- Conceptual depth through academics and capability through hands-on application
- Structured career preparation: portfolio documentation, CV and LinkedIn review, mock interviews, and access to career referrals
Your learning journey
Seven months from technical readiness to career preparation, with academic learning and practical experience running in parallel.
- 1
Weeks 1–2 · Orientation
- 2
From week 3 · Parallel tracks
Learn and apply together
Build theoretical depth while applying it to real AI projects. Both tracks begin together; the practical engagement lasts three months.
Academic track
Learn the foundations
Four self-paced IIIT Kottayam courses · 180 hours · 12 credits.
Live Labs / Internship
Apply your learning
Three months with a partner AI company · Around 20 hours per week · Mentor feedback and peer support.
Theory informs practice; practice deepens understanding
- 3
Towards Live Labs completion
Prepare for opportunities
Document your portfolio, refine your CV and LinkedIn profile, practise technical and HR interviews, and access relevant career referrals.
Present your skills and project experience to employers
Academic Track: Curriculum
Four courses developed and delivered by IIIT Kottayam faculty through pre-recorded instruction, with online subject assessments. Total academic workload: 180 hours. Retain course access for three years from enrolment.
Subject 1
Mathematics for Machine Learning
Subject 1
Mathematics for Machine Learning
Develops the mathematical foundations underlying machine learning: linear algebra for data representation, probability and statistics for modelling uncertainty, and optimization theory that drives model learning.
- •Linear Algebra
- •Probability & Statistics I
- •Probability & Statistics II
- •Statistical Inference
- •Optimization
Subject 2
Data Science with R
Subject 2
Data Science with R
Covers the analytical pipeline from raw data to insight, using R: programming fundamentals, statistical analysis, visualization, preprocessing, and regression.
- •R Programming Fundamentals
- •Statistics & Probability
- •Data Visualization
- •Data Preprocessing
- •Regression & Correlation
Subject 3
Machine Learning: Methods and Applications
Subject 3
Machine Learning: Methods and Applications
Covers the full machine learning workflow: from problem formalization and feature engineering through to model training, evaluation, and debugging, with implementations of the principal supervised learning algorithms.
- •ML Concepts & Workflow
- •Feature Engineering
- •Model Evaluation
- •Linear Models
- •Tree & Instance Methods
- •Support Vector Machines
- •Dimensionality Reduction
Subject 4
Deep Learning and Advanced AI
Subject 4
Deep Learning and Advanced AI
Extends machine learning into deep neural architectures, ensemble techniques, sequential modelling, and natural language processing, with real-world case studies throughout.
- •Clustering
- •Sequential Modelling
- •Neural Networks
- •Ensemble Methods
- •Reinforcement Learning
- •Anomaly Detection
- •NLP with ML
- •Case Studies
Each self-paced IIIT Kottayam course earns you 3 credits, with 12 credits across four courses that can be stacked toward eligible programs in the future.
AI Engineering Live Labs
A three-month practical engagement with a partner AI company runs concurrently with the academic track from Week 3. Students contribute to ongoing projects, collaborate with team members, take on defined responsibilities, and receive regular feedback from their mentor, with additional support from a peer within the company.
- 3 months
- Practical engagement
- ~20 hrs/week
- Weekly commitment
- ~260 hours
- Project experience
Live industry projects
Contribute to ongoing AI projects, collaborate with a company team, and take on defined responsibilities.
Industry mentor guidance
Receive regular feedback and code reviews from your industry mentor, with additional support from a company peer.
For final-year students, this engagement is offered as an industry internship.
Python for AI Engineering
Python for production-grade AI work: data structures for ML, working with APIs, async patterns, code organisation and version control with Git
Large Language Models & GenAI
LLM fundamentals, prompt engineering, embeddings, working with OpenAI and Hugging Face APIs, building LLM-powered applications
Retrieval-Augmented Generation
RAG system design, vector databases (Pinecone, Weaviate, FAISS), document chunking and indexing strategies, evaluation of retrieval quality
Data & AI Pipelines
Building and orchestrating data pipelines, feature stores, batch and streaming data processing, pipeline monitoring
Containers & Deployment
Containerization with Docker, cloud deployment on AWS / Azure / GCP, CI/CD pipelines for ML models, MLflow for experiment tracking
Production AI Applications
End-to-end AI system architecture, API development with FastAPI, serving models with Streamlit or Gradio, monitoring deployed systems
All students work on live datasets, model training, data pipelines, CI/CD, and cloud deployment. Depending on the project assigned, students may also work on RAG systems, large language models, or AI agents. Where a student requires specific technical exposure, the program team can arrange for this through the mentor.
Complete Live Labs to receive an internship/project certificate from the industry partner.
Tools and Technologies
Students work with industry-standard tools across the academic track and Live Labs. The selection below reflects the primary tools used within the program. Specific tools and exposure depend on the assigned project.
Foundations & Programming
- Python
- R
- Jupyter
- Google Colab
- Git / GitHub
Data & Analysis
- NumPy
- Pandas
- SciPy
- Matplotlib
- Seaborn
- Plotly
- MySQL
- PostgreSQL
Machine Learning
- Scikit-learn
- XGBoost
- LightGBM
- CatBoost
- Kaggle
Deep Learning & AI
- TensorFlow
- Keras
- PyTorch
- Hugging Face
- spaCy
- NLTK
- OpenCV
AI Engineering & MLOps
- FastAPI
- Flask
- Streamlit
- Gradio
- MLflow
- Docker
Cloud Platforms
- AWS SageMaker
- Azure AI Studio
- Google Vertex AI
AI Productivity
- ChatGPT
- GitHub Copilot
- Cursor AI
Program Benefits and Credentials
Receive three distinct credentials on successful completion: four subject-level certificates and a Program Certificate from IIIT Kottayam, and a separate internship/project certificate from the industry partner. The IIIT Kottayam certifications cover the academic component; the industry certificate is issued independently by the company where Live Labs are completed.
Subject Completion Certificate
One certificate for each of the four subjects after successful assessment. Certificates carry unique identifiers and are verifiable with IIIT Kottayam.
Program Completion Certificate
The IIIT Kottayam program certificate is awarded after completing all four academic subjects. It covers the academic component of the program.
Industry Internship / Project Certificate
Issued by the industry partner on completion of the Live Labs engagement.
12 stackable credits
Earn 3 credits per self-paced IIIT Kottayam course, with 12 credits across four courses, stackable toward eligible programs.
Who Should Apply
The program is designed for three groups:
- →Final-year students and recent graduates looking to build practical AI engineering skills and a verifiable project portfolio before entering the job market
- →Technology professionals seeking to transition into AI engineering roles or extend their existing technical capabilities into machine learning and AI
- →Developers with experience in other technology stacks, such as web, mobile, or backend, who want a structured path into machine learning, LLMs, and AI engineering
Eligibility
Graduates
Graduates from any discipline who have completed Mathematics at the 12th-standard level.
Final-year students
Students in their final year of an undergraduate program meeting the same mathematics requirement.
Technical readiness
Prior programming experience is beneficial. The two-week orientation phase is designed to bring all students to a common technical starting point before the main program begins.
Take your next step in AI engineering
Inaugural Cohort Price
₹90,000+ taxes
EMI option available
Speak with a Trycle advisor about the Inaugural Cohort Price, your learning goals and the upcoming cohort.