Machine Learning Training in Bangalore – ML Algorithms, Deep Learning & MLOps

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SoftPro9 runs Machine Learning Engineering training from our classroom in BTM Layout 2nd Stage, opposite Infosys, with the same batches streamed live online for learners across Bangalore.

  • Covers: Python, NumPy, pandas, scikit-learn, XGBoost, LightGBM, CatBoost, Optuna and more
  • Mode: Classroom at BTM Layout, live online, or blended
  • New batches: Every Monday and Thursday; IST slots 7 AM / 7:30 PM / 9 PM
  • Duration: 20–24 weeks at 10–12 hours a week, including a production capstone
  • Fee: The current fee is listed on the Machine Learning Engineering course page: /course/machine-learning-ml-training-course. Any cloud ML certification exam is optional and paid directly to the exam provider.
  • Batch size: Up to 15 learners
  • Practice: GPU-enabled cloud notebooks, MLflow tracking server and your own GitHub repositories

Last updated: 28 October 2026

Machine Learning course in Bangalore: basic to advanced

Bangalore has India's deepest pool of ML engineering roles, from recommendation and ranking teams at e-commerce firms to fraud models at fintechs, and they interview hard on fundamentals. The course is split into three levels. You can join at the level that matches your experience after a short assessment at counselling.

Basic

Maths and ML foundations

  • Python, NumPy and pandas for ML work
  • Linear algebra: vectors, matrices, dot products, eigenvectors
  • Calculus for ML: derivatives, gradients and gradient descent
  • Probability, distributions and Bayes' theorem
  • The ML workflow: train/validation/test splits, bias and variance
  • Linear and logistic regression built from scratch, then with scikit-learn
  • Evaluation metrics: RMSE, precision, recall, F1, ROC-AUC

Bangalore practice: UPI and payment-gateway flows tested in sandbox mode.

Intermediate

Algorithms and model building

  • Decision trees, random forests and ensembles
  • Gradient boosting with XGBoost, LightGBM and CatBoost
  • Support vector machines and k-nearest neighbours
  • Clustering (k-means, DBSCAN, hierarchical) and PCA
  • Feature engineering, encoding, scaling and pipelines
  • Hyperparameter tuning with grid search and Optuna
  • Imbalanced data, cross-validation strategies and data leakage
  • Recommender systems: collaborative filtering and matrix factorisation

Bangalore practice: GST invoice data for sales and tax analysis.

Advanced

Deep learning and MLOps

  • Neural networks and backpropagation with PyTorch
  • CNNs for images and sequence models for text and time series
  • Transfer learning and fine-tuning pretrained models
  • Time-series forecasting with ML and deep learning
  • Model explainability (SHAP) and fairness checks
  • MLOps: experiment tracking with MLflow, data versioning with DVC
  • Serving models with FastAPI and Docker; batch versus real-time inference
  • Monitoring drift and retraining; intro to Kubernetes, AWS SageMaker and Google Vertex AI

Bangalore practice: Indian fiscal year (April–March) in reports and time intelligence.

Who joins from Bangalore

  • Service-company engineers on the ORR who want to move to product teams
  • Final-year students from the colleges around Jayanagar, Basavanagudi and Banashankari
  • Non-IT professionals in GCC operations who want a technical role inside the same company

Roles it typically leads to in Bangalore

  • Machine-learning engineer
  • ML / MLOps engineer
  • Data scientist (modelling-focused)
  • Applied ML engineer
  • Computer-vision or recommender-systems engineer

Freshers usually start in junior or support versions of these roles.

Machine Learning Engineering – full course details and fee →

Tools you will use

Every tool below is used hands-on in class or in a project, not just mentioned on a slide.

  • Python
  • NumPy
  • pandas
  • scikit-learn
  • XGBoost
  • LightGBM
  • CatBoost
  • Optuna
  • PyTorch
  • TensorFlow / Keras
  • SHAP
  • MLflow
  • DVC
  • FastAPI
  • Docker
  • Kubernetes (intro)
  • AWS SageMaker
  • Google Vertex AI
  • Git & GitHub
  • Jupyter

Projects you will build

  1. A credit-risk model with tuned gradient boosting, SHAP explanations and a fairness check

  2. A product recommender system evaluated against a popularity baseline

  3. An image classifier fine-tuned from a pretrained CNN

  4. A capstone model served through a FastAPI endpoint in Docker, with MLflow tracking and drift monitoring

  5. Bangalore project: A delivery-time prediction model for a Bangalore quick-commerce service, served as an API, using data and conventions from Bangalore.

Upcoming Bangalore Machine Learning batches

New batches start every Monday and Thursday, with no more than 15 learners in each. Weekday class slots in IST: 7 AM / 7:30 PM / 9 PM. Weekend slots: 10:30 AM / 10:30 PM.

Most working learners take the 7:30 PM weekday batch and come to BTM Layout on Saturday for labs; students prefer the morning or weekend classroom.

Start dateCourseModeBatch size
Thu, 29 Oct 2026Machine Learning (all levels)Classroom + live onlineUp to 15
Mon, 2 Nov 2026Machine Learning (all levels)Classroom + live onlineUp to 15
Thu, 5 Nov 2026Machine Learning (all levels)Classroom + live onlineUp to 15
Mon, 9 Nov 2026Machine Learning (all levels)Classroom + live onlineUp to 15

Message us with the start date and slot you want, and we will confirm your seat.

Reserve on WhatsApp

Machine learning in brief

Machine learning is the part of AI where software learns patterns from data instead of following hand-written rules. A trained model can score a loan application, recommend a product, flag a faulty part or forecast demand, and it improves as it sees more data.

This course goes deeper into the engineering side than a general data science course: how algorithms work under the hood, how to tune and validate them properly, and how to ship, monitor and retrain models in production with MLOps tools such as MLflow, DVC, Docker and cloud ML platforms.

Why machine learning skills matter in Bangalore

Bangalore has the largest concentration of software engineering jobs in India: product companies and startups in Koramangala, HSR Layout and Indiranagar, IT services campuses in Whitefield and Electronic City, and more Global Capability Centres (GCCs) than any other Indian city. That density means more openings, but also more competition, so a visible portfolio matters.

Who hires in Bangalore

  • Product companies and startups

    Koramangala, HSR Layout, Indiranagar and the Outer Ring Road; fintech, SaaS, e-commerce and quick-commerce teams hiring React, Node.js and Python developers.

  • Global Capability Centres

    In-house engineering, analytics and AI teams for banks, retailers and manufacturers headquartered abroad, concentrated on the ORR, Whitefield and Manyata Tech Park.

  • IT services firms

    Large delivery centres in Electronic City and Whitefield that recruit freshers in volume for Python, full-stack and data roles.

  • Research and deep-tech

    Aerospace, semiconductor and biotech firms around the airport, Electronic City and the IISc ecosystem using Python and data science for engineering work.

Indian context you will work with

Generic courses use generic datasets, and interviewers notice. Our exercises include:

  • Datasets in Indian formats: ₹ with lakh/crore grouping, DD-MM-YYYY dates, PIN codes and GSTINs
  • UPI and payment-gateway flows tested in sandbox mode
  • GST invoice data for sales and tax analysis
  • Indian fiscal year (April–March) in reports and time intelligence
  • Kannada and multilingual text in NLP and UI exercises

How to choose the right Machine Learning track

Your backgroundStart withWhy
Software developerFull courseYour engineering habits are what MLOps needs
Data analyst with PythonAlgorithms, then MLOpsMove from reporting to models that run in production
Engineering / maths graduateFull courseThe maths module will be a quick refresher
New to programmingPython firstML assumes you are comfortable writing Python
Mainly interested in ChatGPT-style appsArtificial Intelligence courseThat course focuses on LLMs, RAG and agents

Common pairings: Machine Learning + Python (if you are new to coding), Machine Learning + Artificial Intelligence (for generative AI roles), and Machine Learning + DevOps (for MLOps-heavy roles). Learn one course well before adding a second.

From course to first role: a realistic path

  1. Master the maths and ml foundations before moving on.

  2. Build and publish your projects, including the Bangalore capstone.

  3. Apply for entry roles such as machine-learning engineer or ml / mlops engineer with employers like the product companies and startups above.

Honest note: freshers usually start in junior or trainee roles, and salaries in Bangalore vary too widely for a headline figure. Ask us which openings we are seeing.

Machine Learning certification: what we cover and what we issue

There is no single official machine-learning certification. Cloud vendors run optional exams such as AWS Certified Machine Learning Engineer – Associate, Google Cloud Professional Machine Learning Engineer and Microsoft Azure Data Scientist Associate (DP-100); they are paid directly to the vendor and are not part of our fee. SoftPro9 issues a course completion certificate. Employers mainly judge ML candidates on deployed projects and how well they explain their modelling choices.

What to check before choosing a Machine Learning institute in Bangalore

  • A 2026 syllabus: look for Docker, Kubernetes (intro), AWS SageMaker, Google Vertex AI, not only the basics.

  • Projects on your own accounts, a trainer you can meet first, and a published fee with nothing hidden.

  • No "global certification" or "100% placement" claims: vendors run their own exams, and nobody can promise a job.

How our Machine Learning classes work

  • Classroom at BTM Layout

    Batches are taught live from our BTM Layout centre. Learners within commuting distance attend in person, and anyone can drop in for doubt-clearing during opening hours.

  • Live, with recordings and reviews

    Live sessions in IST, recordings for revision, and project reviews from the trainer. GPU-enabled cloud notebooks, MLflow tracking server and your own GitHub repositories.

  • Interview preparation

    Mock interviews, resume reviews and referrals to Bangalore and remote openings we hear about. We do not guarantee a job.

Machine Learning training across Bangalore: which option suits your area

AreaApprox. distance from BTM LayoutMost learners choose
BTM Layout, Jayanagar, JP Nagar, Bannerghatta Road0–4 kmClassroom
Koramangala, HSR Layout5 kmClassroom or blended
Banashankari, Basavanagudi7–8 kmClassroom or blended
Bellandur, Indiranagar10–11 kmBlended / weekend
Electronic City, Uttarahalli, Vijayanagar12 kmWeekend classroom or online
Malleshwaram, Rajajinagar, Frazer Town13 kmOnline or weekend
Marathahalli, Mahadevapura15–18 kmOnline, weekend for labs
Hebbal, Thanisandra, Whitefield, Yelahanka18–25 kmOnline

Distances are approximate road distances from BTM Layout. Check your own route on Google Maps at your class time; traffic matters more than kilometres here.

Visit our Bangalore centre

SoftPro9 IT Services – Bangalore
22/1, Opp Infosys, BHBCS Layout, BTM Layout 2nd Stage, BTM Layout, Bengaluru, Karnataka – 560076

Phone: +91 95354 51414

Getting here

We are in BTM Layout 2nd Stage, opposite the Infosys office. The nearest metro is Jayadeva Hospital station, about a 10-minute walk away, and BMTC buses on the Outer Ring Road and Bannerghatta Road stop nearby.

Opening hours

Monday–Friday 9:30 AM–7:30 PM · Saturday 9:30 AM–3:30 PM · Sunday closed

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Machine Learning training in Bangalore: frequently asked questions

How much does Machine Learning training cost in Bangalore?

The current training fee is listed on the Machine Learning Engineering course page: /course/machine-learning-ml-training-course. It covers live classes, the practice environment, projects and interview preparation. Any cloud ML certification exam is optional, not included, and paid directly to the exam provider.

How is this different from the Data Science course?

Data Science covers the whole workflow from analysis to modelling and communication. Machine Learning goes deeper into algorithms, tuning and putting models into production with MLOps.

How much maths do I need?

School-level maths is enough to start. We teach the linear algebra, calculus and probability that ML relies on, with code and intuition rather than proofs.

Do you cover MLOps?

Yes. You track experiments with MLflow, version data with DVC, serve models with FastAPI and Docker, and monitor drift.

Do I need a GPU?

No. Deep-learning exercises run in GPU-enabled cloud notebooks we provide.

I live in Whitefield or Hebbal. Is online as good as the classroom?

It is the same trainer, the same live session and the same practice environment. Many learners from north and east Bangalore study online on weekdays and come to BTM Layout on Saturdays for doubt-clearing and mock interviews.

Can I visit the centre before enrolling?

Yes. Walk in during opening hours or book a counselling slot on WhatsApp, meet the trainer and see a class before you pay.

When does the next batch start?

New Machine Learning batches start every Monday and Thursday. See the batch table on this page for the next dates and IST class slots.

Do you guarantee placement?

No. We provide interview preparation, resume help and referrals to openings we hear about in Bangalore, but no institute can honestly guarantee a job.

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Talk to us about your Machine Learning course

Tell us your degree, your current job (if any) and where in Bangalore you are. We will suggest a track and a batch that fits.

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