Ernakulam · Kochi · Online & Weekend

Machine Learning Course in Ernakulam — 14 Weeks, Practical

Last updated: 4 September 2026

This is the most demanding track the academy runs and the only one with a real entry requirement. If you can already write Python comfortably, 14 weeks is enough to build, train and deploy models properly. If you cannot, this page will tell you where to start instead rather than sell you the course anyway.

📍 Campus 45–60 min from Kochi ✓ 14 weeks, practical ✓ ₹31,750 offline / ₹28,250 online ✓ 4-week external internship ✓ Prior programming expected
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Offline Campus 📍

Beeps Digital Academy

A unit of Beeps Digital Private Limited

Near Indira Gandhi Institute of Dental Sciences
Nellikuzhi, Kothamangalam Ernakulam District, Kerala 686691

About 45–60 minutes from Kochi city. Ernakulam learners are served through live online batches and weekend batches at the campus.

📍 Directions 📞 Call
Academy
Beeps Digital - AI & Automation Academy
Operated by
Beeps Digital Private Limited
Training mode
Offline + Online (Hybrid), weekend batches available
Campus
Near IGIDS, Nellikuzhi, Kothamangalam, Ernakulam, Kerala 686691
Courses offered
10 AI and digital tracks, ₹4,750 – ₹31,750
Serving learners in
Kochi, Kakkanad, Edappally, Vyttila, Aluva, Perumbavoor and Ernakulam district
Phone
+91 89218 04806
Email
academy@beepsdigital.com
Beeps Academy runs a 14-week Machine Learning & Deep Learning (Practical) course for Ernakulam and Kochi learners, live online or at its campus in Nellikuzhi, Kothamangalam, about 45–60 minutes from Kochi, with Saturday weekend batches. It costs ₹28,250 online or ₹31,750 offline, includes a 4-week external internship, and expects you to already write Python comfortably.
Read this before anything else

This course has a real prerequisite

Machine learning is the one track here where enthusiasm is not a sufficient starting point. You need to be able to write Python without looking up loops and functions, and you need to be comfortable enough with mathematical notation that a formula on a slide does not stop you. Most people who arrive with an engineering degree and some coding practice are fine. Most people who have never programmed are not, and starting here would waste fourteen weeks and ₹31,750.

If that describes you, the honest recommendation is to start with Data Analytics with AI, which begins from Python basics, covers the same foundational tooling, and leads naturally into ML afterwards. A good number of our ML students took exactly that route. The comparison is set out in more detail in ML vs data analytics.

We would rather turn away an unprepared applicant than take the fee and watch them disengage in week five. If you are unsure where you sit, send us a short description of what you have built and we will tell you plainly.

Syllabus

What fourteen weeks covers

Practical rather than theoretical — every block ends in something that runs, and the maths is introduced where it is needed rather than up front.

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Foundations and the ML workflow
NumPy, Pandas and the parts of linear algebra, probability and calculus that actually recur. Then the workflow itself — splitting data honestly, avoiding leakage, and choosing a metric before you train rather than after you see the result.
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Classical ML with scikit-learn
Linear and logistic regression, decision trees, random forests, gradient boosting, clustering and dimensionality reduction. Feature engineering, cross-validation and hyperparameter tuning. Most production ML in Kerala companies is still this, not deep learning — so it gets the time it deserves.
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Deep learning with TensorFlow and PyTorch
Neural network fundamentals, backpropagation, optimisers and regularisation, built in both frameworks so you are not locked to one. Training on Google Colab, including the practical business of managing runtime limits.
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NLP and transformers
Text preprocessing, embeddings, and the transformer architecture that everything current is built on. Fine-tuning a pretrained model from Hugging Face for a specific task — which is what the work usually is, rather than training from scratch.
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Computer vision
Convolutional networks, transfer learning from pretrained backbones, and image classification and detection on a real dataset. Enough to build a working vision component and to understand why the accuracy number on your test set flatters you.
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MLOps and deployment
The block that separates this from a university module. Packaging a model behind an API, versioning data and models, monitoring for drift, and the reasoning about what happens when a model that worked in March stops working in July. Models that never leave a notebook do not count.
The local picture

What ML work in Ernakulam actually looks like

Worth being realistic about the market you would be entering from Kochi.

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Most roles are applied, not research
The district's demand sits in IT services, product companies at Infopark, fintech and logistics. That means applied modelling on business data far more often than novel research. It is why this course weights scikit-learn and MLOps heavily rather than chasing state-of-the-art architectures.
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ML rarely arrives as a standalone job title
Many local openings describe a data or backend role with a modelling component. Being able to deploy and maintain what you build matters more here than in a research market — a candidate who can ship a model behind an API is more employable than one who can only train it.
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Engineering graduates dominate the pool
You will be competing largely with BTech and MCA graduates, many with the same coursework. What differentiates is a deployed project with a written account of the decisions behind it — which is the specific thing the fourteen weeks is built to produce.
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Remote widens the market considerably
A meaningful share of ML work available to Kochi-based engineers is remote for companies elsewhere. That is worth factoring in, and it is another reason the portfolio and the ability to explain your work matter more than proximity to any particular office.
What you leave with

The portfolio, and the external internship

You finish with a set of artefacts rather than a certificate alone: models on Kaggle, code and READMEs on GitHub, and at least one model published to Hugging Face. Each carries a written account of the problem, the approach and — importantly — what did not work. Reviewers read that section more carefully than the accuracy number, because it is the part that is hard to fake.

The 4-week internship for this track is arranged externally, with partner companies and research partners in the Infopark ecosystem, for the same reason as the analytics track: Beeps Digital is a marketing agency and cannot offer genuine ML infrastructure work in-house. It is included in the fee, carries no separate salary, and ends with a completion certificate and a letter of recommendation. Start dates depend on partner capacity and can shift by a few weeks.

Career support includes a technical mock interview, a portfolio review, and help setting up the Kaggle, GitHub and Hugging Face profiles that this market actually looks at.

Logistics

Attending from Ernakulam

Fourteen weeks is a long commitment, so the mode you choose matters more here than on the shorter tracks.

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Live online — ₹28,250
Trainer-led sessions with recordings within 24 hours. The same syllabus, projects and internship arrangement. Given that the work happens in Colab and a code editor regardless, this mode loses very little for ML specifically.
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Offline at Kothamangalam — ₹31,750
In-person at the Nellikuzhi campus. Worth the travel if you value someone able to look at your training loop when the loss curve does something inexplicable — which, over fourteen weeks, it will.
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Weekend batches
Saturday sessions for people already working at Infopark or Kakkanad. Elapsed time is longer, contact hours and syllabus identical. This is the most common choice among working engineers on this track.
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What you need to bring
A laptop that can run a browser and a code editor. Training runs on Google Colab, so you do not need a GPU machine — we cover working within free-tier runtime limits, and where paying for compute becomes worthwhile. Installment options are available on the fee.
Frequently Asked Questions

Machine Learning Course in Ernakulam — FAQs

Is there a machine learning course in Ernakulam?
Beeps Academy runs a 14-week Machine Learning & Deep Learning (Practical) course serving Ernakulam and Kochi learners. The campus is at Nellikuzhi, Kothamangalam, about 45 to 60 minutes from Kochi, and district learners are served through live online and Saturday weekend batches. The fee is ₹31,750 offline and ₹28,250 online.
Do I need programming experience to join the ML course?
Yes, and this is the only course here with a real prerequisite. You should be able to write Python without looking up basic loops and functions, and be comfortable enough with mathematical notation not to be stopped by a formula. Complete beginners should start with the Data Analytics course, which begins from Python basics and leads naturally into machine learning.
How long is the machine learning course?
Fourteen weeks of taught sessions, followed by a separate 4-week external internship. It is the longest track the academy runs, which reflects the depth of the material rather than a slower pace.
What does the machine learning course cover?
Foundations and the ML workflow, classical machine learning with scikit-learn, deep learning in both TensorFlow and PyTorch, natural language processing with transformers, computer vision, and MLOps including deployment, versioning and drift monitoring. Training runs on Google Colab, so a GPU machine is not required.
What is the fee and are instalments available?
₹31,750 for the offline or weekend batch and ₹28,250 for the fully online batch. Both cover the full 14-week syllabus, the external internship arrangement, a technical mock interview and a portfolio review. Installment options are available.
Where does the ML internship take place?
It is arranged externally with partner companies and research partners in the Infopark and Technopark ecosystem, because meaningful machine learning work needs real infrastructure and data that a marketing agency cannot provide. The 4-week internship is included in the fee, carries no separate salary, and ends with a certificate and a letter of recommendation.
Talk to us

Not sure whether you are ready for this track?

Send us a short description of what you have built in Python so far. We will tell you plainly whether to start here or with the analytics track first.

Questions? academy@beepsdigital.com · +91 89218 04806

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🧠 ML & Deep Learning — full syllabus ⚖️ ML vs Data Analytics 📊 Data Analytics — Kochi & Ernakulam 📍 Data Analytics Course in Kerala 🎓 AI course after BTech 📍 AI Course in Kochi 📍 AI Training in Ernakulam 💰 AI course fees in Kerala 2026 📚 AI Courses in Kerala — all tracks 🧑‍💻 Internship & Projects