Machine Learning & Deep Learning Fundamentals Build
Your first working piece, applying the foundations and the tool setup end to end rather than as isolated exercises.
- Python & Jupyter
- NumPy & Pandas
Learn a job-oriented programme built around live projects rather than theory, taught on live client work at techcadd Phagwara rather than from slides.
techcadd’s Machine Learning & Deep Learning Course After 12th in Phagwara is a one-year programme for students who want to go further than an introductory course takes them. The first stage builds the foundation: Python, the mathematics involved, and statistics applied to real data rather than exam questions.
Key Highlights
techcadd’s Machine Learning & Deep Learning Course After 12th in Phagwara is a one-year programme for students who want to go further than an introductory course takes them. The first stage builds the foundation: Python, the mathematics involved, and statistics applied to real data rather than exam questions. You then work through the standard machine learning models, learning how to prepare features, evaluate honestly and avoid fooling yourself with a good-looking score. The second half is deep learning: how neural networks train, then convolutional networks for images and sequence models for text, with transfer learning covered because training from scratch is rarely the right call. Later modules deal with deploying a model and monitoring it once it is running. Sessions are hands-on, with a trainer reviewing both your code and your reasoning. You finish with trained models you can explain, a portfolio and interview preparation.
Every module ends in something you have built and a trainer has reviewed, so the list below is work you will have done rather than topics you will have heard about.
missing values, imbalanced classes, images and text — prepared before anything is trained on them
The syllabus is arranged so every module produces an asset rather than a set of notes. You will cover stage 1 — foundations & environment, stage 2 — techniques, workflows & real data, stage 3 — standards & the live build, stage 4 — review, portfolio & placement, and finish with a live project built on Python & Jupyter, NumPy & Pandas, scikit-learn. Modules run in the order a real project runs: foundations first, then the core skills, then applied work under supervision, then the portfolio and interview preparation that turn all of it into an offer letter.
The working knowledge the job description actually lists.
Stage 2 — Techniques, Workflows & Real Data
The working loop, applied to inputs that arrive imperfect.
2–3 months · 48 sessions
Topics covered
The toolchain
Everything below is installed on the lab machines and used on live client work, not shown once in a slide and forgotten.
Join from any stream. You start from fundamentals with no assumed knowledge, and most students run the course alongside a degree at a Phagwara college using the weekday or weekend batch.
If you are finishing a BA, BBA, B.Com, BCA or B.Tech, this is the shortest route from degree to salary. Enter placement season with project work in hand instead of a blank CV.
The weekend batch exists for people already earning. Career switchers typically become interview-ready for Trainee Executive roles within five to six months without leaving their current job.
Owners take this course to stop outsourcing work they cannot judge. Freelancers take it to bill clients beyond Punjab, since location does not limit remote work in this field.
A gap on the CV counts for less than work you can point at. The course starts at zero and finishes with a portfolio and a documented internship letter, which is what an interviewer asks about after a break.
If free videos left you with notes but nothing built, what changes here is a trainer who reviews what you produced this week and a deadline attached to every module.
Anyone can fit a model; far fewer can tell you honestly whether the score means anything, and that judgement is what the second half of this course is for. That gap is the whole argument for this course: there is local demand, there are budgets, and there are very few trained people to hand the work to.

Build skills that hold up beyond the classroom.
What separates this from a playlist of tutorials is supervision on real work. From the second half of the course you build on live client projects with a trainer beside you, make decisions that have consequences, and correct them the following week. That loop is the skill. No employer in Phagwara will take your word for it without work they can inspect.
Be realistic about the money. A fresher who finishes with a working portfolio starts near the bottom of the band and moves quickly; someone who finishes with a certificate and nothing to show does not. The difference is entirely what you built.
The alternative is what most people try first: free videos, a cheap online course, six months of drifting, and knowledge you cannot demonstrate. A structured programme with live projects, a mentor who corrects you, an internship letter and a placement cell that actually calls employers is the difference between knowing the subject and being hired to do it.
Students reach the Phagwara centre from Banga, Nakodar, Kartarpur and the university belt, and the weekend batch exists so a job or a degree does not have to be paused to attend.
Employers here consistently ask for demonstrable project work over certificates alone. That gap is the whole argument for this course: there is local demand, there are budgets, and there are very few trained people to hand the work to.
What separates this from a playlist of tutorials is supervision. From the second half of the course you build on live client projects with a trainer beside you, make decisions that have consequences, and correct them the following week. That loop is the skill.
A fresher who finishes with a working portfolio typically starts around ₹15,000 – ₹28,000 a month locally, and moves up quickly with experience. The ceiling is high, but it is earned — nobody pays a beginner well for a certificate alone.
The alternative is what most people try first: free videos, a cheap online course, six months of drifting, and knowledge you cannot demonstrate. A mentor who corrects you, an internship letter and a placement cell that actually calls employers is the difference between knowing the subject and being hired to do it.

Complete the course with a portfolio of live projects and receive an industry-recognised certificate, plus a documented internship letter accepted by Punjab universities.
Recognised by employers across Punjab and beyond
Based on real client work, not a simulation
Live work you can show in any interview
CV review, mock interviews and hiring drives
Two certificates on completion — the course certificate and a separate capstone project certificate.
The roles this opens, what they pay in Punjab and beyond, and who is hiring for them — drawn from published job-market listings, not a brochure number.
Salary outlook — Junior ML Engineer
Pay here follows the portfolio rather than the certificate. With two years of delivery experience the starting figure typically doubles, and specialists who keep learning move well beyond it.
Indicative ranges compiled from public job-market listings. Actual offers vary by employer, skillset and interview performance.
Your first working piece, applying the foundations and the tool setup end to end rather than as isolated exercises.
Work with messy, real inputs against industry standards and best practice — and defend the choices you made to a trainer.
A genuine requirement from techcadd’s delivery pipeline, scoped, built and shipped under supervision. This is the one interviewers ask about.
A machine learning & deep learning project you specify yourself, covering testing, review, iteration and deployment, and present as your final piece.
Every project moves through the same loop: understand the brief, build with guidance, then explain the decisions behind your work.
Take a real requirement apart before touching a tool — what is being asked, what it needs, and which part to build first.
Machine Learning & Deep Learning Fundamentals Build
Work hands-on with your trainer watching the screen, so a wrong turn is caught in the same session rather than three weeks later.
Real-World Data Challenge
Walk through what you built and why you built it that way. This is the interview rehearsal, run against every project rather than once at the end.
Live Client Brief
There are many places to learn this in Phagwara 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.
Your trainer is not a full-time lecturer. They deliver client projects for techcadd’s services arm, so examples in class are current rather than a case study from five years ago.
You work on genuine client requirements under supervision. This 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 Phagwara, Jalandhar and Ludhiana, 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 our certificate means.
Find answers to the questions students ask before enrolling.
techcadd runs Machine Learning & Deep Learning over 6 Months – 1 Year. Weekday, evening and weekend batches cover the same syllabus, and 1-on-1 training is available if you would rather set your own pace. Every class runs for 2 hours, whichever format you choose.

Send your question and a counsellor will call you back about batch timings, fees, EMI options, placement record, or whether this course fits your degree.
One call with a counsellor is usually enough to find out. Book a free demo class and see the lab before you decide.