Exploratory Analysis
A full EDA notebook on a real dataset with cleaned data and visual findings.
- pandas
- scikit-learn
- TensorFlow
Programme at a glance
6 months
Duration
6
Structured blocks
4
Live projects
Included
Internship letter
Short on time? 45 days / 6 weeks Data Science training fits a summer break or your college's 6 weeks industrial training with one focused live project.
45 days · 6 weeks
Six weeks to go from Python basics to one trained and deployed ML model.
45 days – 6 months
Python, statistics and machine learning, ending in a deployed model on real data.
techcadd's 6 Months Data Science Training in Amritsar is aimed at students, graduates and working professionals — whatever they have or have not done before. The early modules cover Python for Data Science, Statistics & Probability and Exploratory Data Analysis, so nothing later assumes knowledge you were never given. From there you take on Machine Learning and Deep Learning Basics. The second half is where it turns practical: you work in Python 3, NumPy, pandas, scikit-learn, TensorFlow and Jupyter the way a team actually does, against briefs that carry a real deadline. Each module ends in something you have built and a trainer has reviewed, so you finish with a portfolio, a CV built around it and interview practice for Junior Data Scientist, Machine Learning Trainee and Data Analyst roles.
Doing your 6 months internship or training semester? Spend it going deep on Data Science. A data scientist is hired to build models that hold up on data they have not seen. This training covers the full workflow — collecting and cleaning data, exploring it, training and evaluating models, and deploying one — on real datasets rather than tidy textbook examples.
Built for B.Tech, BCA, MCA and final-year students with a 6 months internship or training semester, this programme covers the complete Data Science track — Python for Data Science through Model Deployment — on Python 3, NumPy, pandas and scikit-learn, and finishes with a capstone project and a project report in your department's format.
The live brief is a prediction problem from our client pipeline, taken through to a deployed model with a Streamlit interface. You leave with a notebook, a deployed demo and a letter that names the project.
Reviewed by mentors · built for interviews
Live client work from week one, at the Amritsar lab.
No block is padding and none of it is a lecture series. Each span below ends in something a trainer has signed off on.
Python, NumPy and pandas, then statistics and exploratory analysis on real datasets, worked daily with a trainer reviewing your notebooks.
A real prediction brief: features engineered, models trained and evaluated with scikit-learn, and the best one tuned, reviewed in daily increments.
The model deployed with Streamlit, a project write-up, then the certificate, the letter and a mock data-science interview.
Python for Data Science is where the 6 Months Data Science Training track gets its footing. You work the concepts in the lab first, then carry them straight into the running project rather than leaving them as isolated exercises.
A reviewed piece of work demonstrating numpy arrays and pandas dataframes.
This block turns statistics & probability from something you have read about into something you can do under time pressure, with a mentor reviewing the work as you go.
A reviewed piece of work demonstrating distributions and hypothesis testing.
By the end of exploratory data analysis, you can make the calls a working 6 months data science training practitioner makes daily — and explain why you made them.
A reviewed piece of work demonstrating cleaning and outliers and visualisation.
Machine Learning is taught against realistic, imperfect inputs. The point is not the clean textbook case; it is what you do when the data or the requirement fights back.
A reviewed piece of work demonstrating regression and classification and clustering.
Everything in deep learning basics feeds the next stage of the 6 months data science training build, so nothing here is theory you park and forget.
A reviewed piece of work demonstrating neural networks and tensorflow intro.
You leave model deployment with a reviewed artefact in your portfolio, not just notes — that is the standard every module in this course is held to.
A deployed model with its notebook and evaluation.
There is no entrance test and no prerequisite degree. What the programme does assume is that you will show up for the full 6 months and do the project work.
Nothing is assumed beyond a 12th pass and comfort with a computer. 6 Months Data Science Training is often the first thing on an otherwise empty CV, which is exactly why it ends in a reviewed project rather than a certificate alone.
If your syllabus mandates training, this satisfies it — and unlike a signature on a form, you leave with work you can show. Most of each intake is in their final year or just out of it.
Two-hour classes either side of a working day, or a weekend batch across 6 months. You are not asked to resign to retrain, and the project work is scheduled around the batch you pick.
You are here for the specific thing you keep paying someone else to do. The live brief can usually be your own requirement rather than ours, so the training pays for itself once.
A gap on a CV is only a problem if there is nothing to put in it. 4 reviewed projects and a documented letter turn 6 months into an answer rather than a question.
You can already build something; what is missing is the review, the conventions and the evidence. You skip the early blocks fast and spend the time saved on the live brief.
Job titles vary by company, but the underlying expectations do not. Each destination below maps to work you will have already done during the programme.
Complete the programme with a portfolio of live projects and receive an industry-recognised certificate, plus a documented internship letter accepted by Punjab universities.
Industry Certificate
Recognised by employers across Punjab and beyond
Internship Letter
Based on real client work, not a simulation
Portfolio of Projects
Live work you can show in any interview
Placement Support
CV review, mock interviews and hiring drives — support, not a guarantee
Two documents on completion — the course certificate, and a separate internship letter describing the live work you did.
A certificate answers what you can do today. This is the honest answer to what 6 months data science training looks like three to five years out, and why the fundamentals this course spends real time on are what carry you there.
The 6 months programme is built around the part that is genuinely in your hands — and you leave holding all of it.
A reviewed portfolio, an industry-recognised certificate and a fundamentals-first foundation you can keep building on. Markets move, as they always have; that foundation is exactly what lets you move with them as internship and training work around you keeps shifting.
A full EDA notebook on a real dataset with cleaned data and visual findings.
A regression model with feature engineering and a clear evaluation.
A real problem from the techcadd client pipeline, solved with a trained model.
Your best model served through a Streamlit app anyone can try.
Every project moves through the same loop: understand the brief, build it with guidance, then explain the decisions behind your work. The certificate is the receipt — the portfolio is the point.
Break a real requirement into a plan, the constraints it has to live inside, and the right tool for each part of it.
Exploratory Analysis
Work hands-on with trainer feedback arriving while the decisions are still cheap to change.
Price Prediction Model
Turn the finished work into a portfolio story you can defend line by line in an interview.
Live Prediction Brief
There are many places to learn this in Amritsar, and the brochure syllabus looks similar at all of them. What differs is who teaches, whether you ever touch real work, and whether anyone picks up the phone after you have paid. techcadd has trained students across Punjab since 2007 on the same model: small batches, working practitioners as trainers, client projects as coursework — and 6 Months Data Science Training runs on exactly that model.
Your trainer is not a full-time lecturer. They deliver client projects for the techcadd services arm, so the examples in class are current rather than a case study from five years ago.
You work on genuine client requirements under supervision. That is where a portfolio comes from, and it is the first thing an interviewer asks to see.
Batches stay small enough that a trainer sees your screen daily. Lab time runs outside class hours, and doubt sessions continue until the concept lands.
Every student finishes with an industry-recognised certificate and a documented internship on real work, accepted for university industrial training requirements.
Mock interviews, CV reviews and drives with hiring partners across Amritsar and Punjab — repeated after a rejection, not abandoned.
Nearly two decades of hiring relationships in Punjab is why a call from our placement cell gets answered, and why local employers know what a techcadd certificate means.
Collected from students who completed the 6 months data science training programme at the Amritsar campus, across morning, evening and weekend batches. Hover a card to slow the row right down and read it.
4.7
out of 5
162 verified reviews from Amritsar students
I joined the 6 Months Data Science Training batch with almost no background, and what made the difference was that python for data science was taught by building rather than by slides. By the third week I was debugging my own code instead of copying someone else's.
The project reviews are the real value. My price prediction model was picked apart line by line, and those notes are exactly what I ended up talking through in the interview that got me a machine learning trainee offer.
Weekend batches meant I kept my job through the whole 6 months. Anything I missed got re-explained without fuss, and lab access outside batch hours was never a problem.
NumPy and the rest of the stack were set up on day one, so no week went into environment issues. Batches are small enough that a doubt gets answered the same day instead of piling up.
I had tried learning 6 months data science training on my own twice and stalled both times. A fixed batch in Amritsar, a mentor who checks your work and a deadline on every module is the only reason I finished.
Placement support was not just a line on the brochure — resume and portfolio review, two mock interviews with people who do the job, and a referral into one of the hiring drives.
The syllabus is current. We worked in Python 3 rather than the older tooling most 6 months data science training syllabi around here still teach, and that came up directly in my first interview.
The balance of theory to lab time is about right: enough to understand why something works, then straight into building. I left with 4 projects I can demo, not just a certificate.
If something here is not covered, the Amritsar desk will answer it directly — no call-back queue.
A semester-long Data Science internship — foundations first, then live briefs across the full track, then a capstone project and placement prep. The full data science track over six months, including deep learning and a capstone project you can demo.
One call with a counsellor is usually enough to find out. Book a free demo class and see the Amritsar lab before you decide.
45 days summer or winter training in Amritsar for B.Tech, BCA, MCA and diploma students — one live project, daily mentor reviews and an internship certificate, all inside your vacation.
45 days · 6 weeks6 weeks industrial training in Amritsar for B.Tech, BCA, MCA and diploma students — the university-mandated slot done properly, with a live project, daily trainer sign-off and a report in your college's format.
6 weeksIndustry-driven, hands-on training for engineering and IT students who want real skill — two live briefs, a capstone, and the toolchain habits that survive a real job.
4 monthsSend your question and a counsellor will call you back about batch timings, fees, EMI options, placement record, or whether this course fits your background.
Book a free demo class and see the lab before you decide.