BUILD THE INTELLIGENCE
Artificial Intelligence & Machine Learning.
Machine learning, deep learning and deployment foundations.
Explore machine learning, neural networks, LLM architecture, computer vision and cloud deployment through small model-building projects. An engineering foundation—not a promise to master every AI field in three months.
Request enrollmentBatch dates, venue and timings are confirmed with admissions before you join.
Teaching is in English. Explanations in Kannada and Tulu are available for students who prefer them to help deepen their understanding.
Approximately 12 sessions and 24 teaching hours, plus practical work between sessions.
Pay after each completed month. ₹18,000 including taxes for three months. Additional foundation months are ₹6,000 each, including taxes. No upfront payment.
In-person venue: HexAI Labs, Lotus Paradise Centre, Karangalpady KRR Road, Bunts Hostel Road, Mangaluru (Mangalore), Karnataka 575003. View directions ↗
From training data to a deployed model.
Define the task, prepare representative data and keep a separate test set.
01 / THE OUTCOME
Train a model. Understand its limits.
A small trained model with an evaluation report and cloud deployment plan or endpoint, alongside guided language and vision experiments.
02 / YOUR WEEKLY OUTLINE
Your learning, week by week.
Approximately 12 sessions and 24 live hours. Plan for 2–4 hours of practical work between weekly sessions; project effort will vary.
01The AI engineering landscape+
Connect AI, ML and deep learning. Review Python, data and the mathematics used in the programme.
02Data before models+
Prepare datasets, separate training and test data, understand leakage and choose metrics.
03Train your first ML model+
Build regression and classification baselines and understand features, loss and generalization.
04Evaluate and improve+
Compare models, inspect errors, recognize overfitting and document dataset limitations.
05Neural network foundations+
Understand layers, gradients and training loops through a small neural-network exercise.
06Computer vision+
Explore image classification and transfer learning through a small vision experiment.
07LLMs and transformer architecture+
Explore tokens, embeddings and attention, and how transformers support language modeling.
08Build a tiny language model+
Follow a small educational model-building exercise. Understand why frontier-scale pretraining is outside the scope and budget of this programme.
09Adapt an existing model+
Compare prompting, retrieval and fine-tuning. Explore a small adaptation experiment within available compute limits.
10Serve models in the cloud+
Package inference behind an API, manage configuration and secrets, and estimate compute costs.
11Production foundations+
Explore versioning, monitoring, drift, latency, access controls and rollback planning.
12Demonstrate your model project+
Present a model, evaluation evidence, limitations and deployment approach. Explain what would be needed for real production use.
03 / LEARNING BY DOING
Build something you can show.
Example project ideas to show the kind of work you can practise. These are not past learner results.
A trained and evaluated prediction model
A small language-model or vision experiment
A model-serving API with documented limitations
04 / FIND YOUR FIT
Who this programme is for.
Who it’s for
Beginners, CS and non-CS learners, developers and domain professionals who want to build AI models. No prior coding experience or particular degree is required; we teach the foundations step by step.
Before you begin
No prior coding or advanced mathematics experience required. We teach the Python and mathematical foundations needed for the programme.
Foundation training and your learning timeline
The main programme runs for three months. Foundation training is tailored to your starting point and progress; some learners may need one or two additional months to build a stronger understanding. Membership is ₹6,000 per month including taxes, payable after each completed month, including any additional foundation months. The team will discuss your learning plan and timing with you before you opt for additional months.
Plan for 2–4 hours of practice each week outside live sessions as a starting guideline. Beginners may need more time for foundation exercises and projects; we’ll help you plan a manageable practice routine based on your progress.
05 / THE WEEKLY RHYTHM
Learn it. Try it.
Come back with better questions.
Understand the approach
Use your two live hours to explore concepts, follow demonstrations and ask why a particular approach works.
Work through the friction
Plan for 2–4 hours of practical work between weekly sessions; project effort will vary. Keep notes on what worked, what failed and what you need to understand next.
Make the work stronger
Bring questions into the next session. Revisit assumptions, test another case and improve your project step by step.
06 / A PROJECT WORTH SHOWING
More than a polished demo.
Your final project should make your reasoning visible—not just produce an impressive screen.
A clear problem
Who is this for? What task does it improve? Describe the starting point and the result you are aiming for.
Evidence it works
Show realistic test cases, quality checks and where the approach still fails.
Responsible boundaries
Explain data handling, limitations and which decisions should stay with a person.
A usable handover
Document how to use your work so someone else can understand and reproduce it.
07 / COMPLETION & NEXT STEPS
Complete your course.
Learn to present your skills.
Your course completion certificate
On completing Artificial Intelligence & Machine Learning, you receive a HexAI Labs course completion certificate. This recognises completion of your programme and is separate from the optional assessed certification below.
Two additional weeks. No membership fee.
After your course ends, you can attend two additional weeks of interview and presentation skills training. Practise explaining your work, presenting your projects and communicating your approach in an interview. No membership fee is charged for these two weeks; the team will share the session schedule.
08 / OPTIONAL SKILLS CERTIFICATION
Demonstrate what you can do.
HexAI Labs — Certified Applied AI & ML Practitioner
LABSA RECOGNITION OF DEMONSTRATED SKILL
Certified Applied AI & ML Practitioner
Issued by HexAI Labs after passing all four assessments
Available exclusively to learners who have completed the relevant course with HexAI Labs, this is a separate assessment-based certification—not an additional course or the course completion certificate. The certification assessment fee is ₹3,600 per attempt, including taxes, separate from monthly membership and the free two-week skills training.
Interview assessment
Explain your understanding, decisions and approach to course-related problems.
Presentation assessment
Present your project clearly, demonstrate your work and respond to questions.
Written skills assessment
Show your understanding of the concepts and reasoning covered in your programme.
Practical skills assessment
Apply your learning to a hands-on task relevant to your programme.
A record of your assessed skills
Only after passing all four assessments—interview, presentation, written skills and practical skills—will you receive the HexAI Labs Certified Applied AI & ML Practitioner certificate and a reference letter with a SWOT report covering strengths, weaknesses, opportunities and threats relevant to your skills development. Participation or payment alone does not qualify you for these awards. Ask the team for the assessment criteria before booking an attempt.
These are HexAI Labs-issued credentials, not third-party or government-accredited qualifications. Certification and skills training do not guarantee employment or placement.
09 / SET YOURSELF UP
Bring curiosity.
Make room for practice.
A laptop, a reliable internet connection and a regular practice slot will help you get more from the programme. Bring a real task you care about, without sharing private employer or customer data.
Some exercises may use third-party AI tools or APIs. Ask our team about free alternatives and potential usage costs before your batch begins. This programme does not guarantee a job or income.
Before you request enrollment.
How will this programme support my career preparation?+
Build practical work you can demonstrate, then practise explaining it through two additional weeks of interview and presentation skills training after course completion, with no membership fee for those two weeks.
You can also choose the optional HexAI Labs Certified Applied AI & ML Practitioner assessment at ₹3,600 per attempt, including taxes. Passing all four assessments earns you the certification certificate and a reference letter with a SWOT report to help you present your skills and identify areas for growth.
Our focus is helping you prepare for opportunities. Hiring decisions remain with employers and depend on role requirements, your demonstrated skills and the selection process.
When does the next batch start?+
Our team will share available batch dates, weekly days, and time slots during your admissions call. Your confirmed schedule will appear in your learner portal.
What are the fees and duration?+
The main programme lasts three months with two live hours weekly. The standard membership is ₹6,000 including taxes after each completed month. Completing all three months at the standard membership totals ₹18,000 including taxes, paid monthly—not upfront. Any additional foundation months are ₹6,000 each, including taxes. You can choose to leave; contact our team to discuss withdrawal and any outstanding dues.
What happens after I apply?+
We acknowledge your request and contact you to discuss your goals and available batches. If you decide to proceed, we arrange a registration appointment. Your place is confirmed once registration and batch assignment are complete; a request alone does not reserve a seat.