Deep LearningMost In-Demand
The deep learning skillset Punjab's growing AI and analytics teams are hiring for right now.
A six-month, project-driven programme that takes you from Python and data foundations through machine learning, then into deep learning — neural networks, CNNs and RNNs — built with TensorFlow and Keras. Every module ends in a deliverable you can show an employer, reviewed by mentors who still work on live projects. Small batches, weekday or weekend options, and placement support from a campus on Ferozepur Road.
Admissions open
Free demo class & counselling
Batch slots
Course overview
IT services firms, product companies and analytics teams across Ludhiana, Mohali and Jalandhar hire deep learning and ML developers — typically after checking a working model project, not a certificate.
Curriculum
The six-month programme is built as a ladder, not a set of parallel topics — each module depends on the one before it, and each ends in a deliverable. Months 1–2 build programming and data foundations, month 3 covers classical machine learning, month 4 moves into deep learning, and months 5–6 cover applied deep learning, deployment and the capstone.
Build core programming logic, clean code structure, debugging fundamentals and object-oriented thinking in Python.
Topics covered
You finish with
Write and debug small Python programs and automation scripts independently.
Learn data wrangling, visualization, and business intelligence — from cleaning raw data in Python to querying databases with SQL and building dashboards in Power BI.
Topics covered
You finish with
Train, e A complete exploratory data analysis report and an interactive Power BI dashboard on a real dataset.valuate and compare machine learning models on a real dataset.
Learn how to choose, train, tune and validate classical machine learning models on real datasets.
Topics covered
You finish with
A deployment-ready machine learning project with documented results and model comparison.
Design and train neural networks for vision and sequence tasks using TensorFlow and Keras.
Topics covered
You finish with
A deep learning project — an image or sequence classifier built and evaluated.
Consolidate your skills into a single capstone project, build your professional portfolio, and prepare for technical interviews.
Topics covered
You finish with
A complete flagship deep learning project, portfolio and interview-ready profile.
Every module includes hands-on practice on a real dataset or a real deliverable, not a slide demonstration.
What you learn
The Deep Learning Course in Ludhiana at Techcadd is designed to help students move from basic programming concepts to building, training, and deploying practical neural networks.
Write clean, object-oriented Python code from scratch. You will learn to handle files, debug errors, and automate tasks using functions and data structures.
Clean and analyze real datasets using Pandas and NumPy, query databases with SQL, and build interactive KPI dashboards using Power BI.
Train, evaluate, and tune predictive models including Linear Regression, Random Forest, SVM, and K-Means clustering using Scikit-learn.
Build and train Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Recurrent Neural Networks (RNN) using TensorFlow and Keras.
Take models out of the notebook and deploy them as interactive web applications using Streamlit and Flask, complete with API integration.
Tools you’ll work with
The objective is practical knowledge rather than memorised concepts — you finish with trained models you can show and code you can defend.
Find your pace
The Deep Learning syllabus in the order you meet it, and what you are able to do by the end of each stretch of it. Every row is a capability, not a topic you sat through.
| Capability | Python & Programming Foundation | Data Analytics, SQL & Power BI | Machine Learning | Deep Learning & Neural Networks | Applied Deep Learning & Model Deployment | Major Project & Career Preparation |
|---|---|---|---|---|---|---|
| PythonPython & Programming Foundation | Covered in Python & Programming Foundation | Covered in Data Analytics, SQL & Power BI | Covered in Machine Learning | Covered in Deep Learning & Neural Networks | Covered in Applied Deep Learning & Model Deployment | Covered in Major Project & Career Preparation |
| VariablesPython & Programming Foundation | Covered in Python & Programming Foundation | Covered in Data Analytics, SQL & Power BI | Covered in Machine Learning | Covered in Deep Learning & Neural Networks | Covered in Applied Deep Learning & Model Deployment | Covered in Major Project & Career Preparation |
| Data typesPython & Programming Foundation | Covered in Python & Programming Foundation | Covered in Data Analytics, SQL & Power BI | Covered in Machine Learning | Covered in Deep Learning & Neural Networks | Covered in Applied Deep Learning & Model Deployment | Covered in Major Project & Career Preparation |
| LoopsPython & Programming Foundation | Covered in Python & Programming Foundation | Covered in Data Analytics, SQL & Power BI | Covered in Machine Learning | Covered in Deep Learning & Neural Networks | Covered in Applied Deep Learning & Model Deployment | Covered in Major Project & Career Preparation |
| FunctionPython & Programming Foundation | Covered in Python & Programming Foundation | Covered in Data Analytics, SQL & Power BI | Covered in Machine Learning | Covered in Deep Learning & Neural Networks | Covered in Applied Deep Learning & Model Deployment | Covered in Major Project & Career Preparation |
| File HandlingPython & Programming Foundation | Covered in Python & Programming Foundation | Covered in Data Analytics, SQL & Power BI | Covered in Machine Learning | Covered in Deep Learning & Neural Networks | Covered in Applied Deep Learning & Model Deployment | Covered in Major Project & Career Preparation |
| Exception HandlingPython & Programming Foundation | Covered in Python & Programming Foundation | Covered in Data Analytics, SQL & Power BI | Covered in Machine Learning | Covered in Deep Learning & Neural Networks | Covered in Applied Deep Learning & Model Deployment | Covered in Major Project & Career Preparation |
| OOPPython & Programming Foundation | Covered in Python & Programming Foundation | Covered in Data Analytics, SQL & Power BI | Covered in Machine Learning | Covered in Deep Learning & Neural Networks | Covered in Applied Deep Learning & Model Deployment | Covered in Major Project & Career Preparation |
| NumpyData Analytics, SQL & Power BI | Covered in Python & Programming Foundation | Covered in Data Analytics, SQL & Power BI | Covered in Machine Learning | Covered in Deep Learning & Neural Networks | Covered in Applied Deep Learning & Model Deployment | Covered in Major Project & Career Preparation |
| PandasData Analytics, SQL & Power BI | Covered in Python & Programming Foundation | Covered in Data Analytics, SQL & Power BI | Covered in Machine Learning | Covered in Deep Learning & Neural Networks | Covered in Applied Deep Learning & Model Deployment | Covered in Major Project & Career Preparation |
| SeabornData Analytics, SQL & Power BI | Covered in Python & Programming Foundation | Covered in Data Analytics, SQL & Power BI | Covered in Machine Learning | Covered in Deep Learning & Neural Networks | Covered in Applied Deep Learning & Model Deployment | Covered in Major Project & Career Preparation |
| MatplotlibData Analytics, SQL & Power BI | Covered in Python & Programming Foundation | Covered in Data Analytics, SQL & Power BI | Covered in Machine Learning | Covered in Deep Learning & Neural Networks | Covered in Applied Deep Learning & Model Deployment | Covered in Major Project & Career Preparation |
| EDAData Analytics, SQL & Power BI | Covered in Python & Programming Foundation | Covered in Data Analytics, SQL & Power BI | Covered in Machine Learning | Covered in Deep Learning & Neural Networks | Covered in Applied Deep Learning & Model Deployment | Covered in Major Project & Career Preparation |
| SQLData Analytics, SQL & Power BI | Covered in Python & Programming Foundation | Covered in Data Analytics, SQL & Power BI | Covered in Machine Learning | Covered in Deep Learning & Neural Networks | Covered in Applied Deep Learning & Model Deployment | Covered in Major Project & Career Preparation |
| Power BIData Analytics, SQL & Power BI | Covered in Python & Programming Foundation | Covered in Data Analytics, SQL & Power BI | Covered in Machine Learning | Covered in Deep Learning & Neural Networks | Covered in Applied Deep Learning & Model Deployment | Covered in Major Project & Career Preparation |
| Machine LearningMachine Learning | Covered in Python & Programming Foundation | Covered in Data Analytics, SQL & Power BI | Covered in Machine Learning | Covered in Deep Learning & Neural Networks | Covered in Applied Deep Learning & Model Deployment | Covered in Major Project & Career Preparation |
| RegressionMachine Learning | Covered in Python & Programming Foundation | Covered in Data Analytics, SQL & Power BI | Covered in Machine Learning | Covered in Deep Learning & Neural Networks | Covered in Applied Deep Learning & Model Deployment | Covered in Major Project & Career Preparation |
| ClassificationMachine Learning | Covered in Python & Programming Foundation | Covered in Data Analytics, SQL & Power BI | Covered in Machine Learning | Covered in Deep Learning & Neural Networks | Covered in Applied Deep Learning & Model Deployment | Covered in Major Project & Career Preparation |
| Naive BayesMachine Learning | Covered in Python & Programming Foundation | Covered in Data Analytics, SQL & Power BI | Covered in Machine Learning | Covered in Deep Learning & Neural Networks | Covered in Applied Deep Learning & Model Deployment | Covered in Major Project & Career Preparation |
| Grid SearchMachine Learning | Covered in Python & Programming Foundation | Covered in Data Analytics, SQL & Power BI | Covered in Machine Learning | Covered in Deep Learning & Neural Networks | Covered in Applied Deep Learning & Model Deployment | Covered in Major Project & Career Preparation |
| Cross ValidationMachine Learning | Covered in Python & Programming Foundation | Covered in Data Analytics, SQL & Power BI | Covered in Machine Learning | Covered in Deep Learning & Neural Networks | Covered in Applied Deep Learning & Model Deployment | Covered in Major Project & Career Preparation |
| Deep LearningDeep Learning & Neural Networks | Covered in Python & Programming Foundation | Covered in Data Analytics, SQL & Power BI | Covered in Machine Learning | Covered in Deep Learning & Neural Networks | Covered in Applied Deep Learning & Model Deployment | Covered in Major Project & Career Preparation |
| CNNDeep Learning & Neural Networks | Covered in Python & Programming Foundation | Covered in Data Analytics, SQL & Power BI | Covered in Machine Learning | Covered in Deep Learning & Neural Networks | Covered in Applied Deep Learning & Model Deployment | Covered in Major Project & Career Preparation |
| RNNDeep Learning & Neural Networks | Covered in Python & Programming Foundation | Covered in Data Analytics, SQL & Power BI | Covered in Machine Learning | Covered in Deep Learning & Neural Networks | Covered in Applied Deep Learning & Model Deployment | Covered in Major Project & Career Preparation |
| ANNDeep Learning & Neural Networks | Covered in Python & Programming Foundation | Covered in Data Analytics, SQL & Power BI | Covered in Machine Learning | Covered in Deep Learning & Neural Networks | Covered in Applied Deep Learning & Model Deployment | Covered in Major Project & Career Preparation |
| FNNDeep Learning & Neural Networks | Covered in Python & Programming Foundation | Covered in Data Analytics, SQL & Power BI | Covered in Machine Learning | Covered in Deep Learning & Neural Networks | Covered in Applied Deep Learning & Model Deployment | Covered in Major Project & Career Preparation |
| TensorflowDeep Learning & Neural Networks | Covered in Python & Programming Foundation | Covered in Data Analytics, SQL & Power BI | Covered in Machine Learning | Covered in Deep Learning & Neural Networks | Covered in Applied Deep Learning & Model Deployment | Covered in Major Project & Career Preparation |
| KerasDeep Learning & Neural Networks | Covered in Python & Programming Foundation | Covered in Data Analytics, SQL & Power BI | Covered in Machine Learning | Covered in Deep Learning & Neural Networks | Covered in Applied Deep Learning & Model Deployment | Covered in Major Project & Career Preparation |
| End-to-End Deep Learning Major ProjectMajor Project & Career Preparation | Covered in Python & Programming Foundation | Covered in Data Analytics, SQL & Power BI | Covered in Machine Learning | Covered in Deep Learning & Neural Networks | Covered in Applied Deep Learning & Model Deployment | Covered in Major Project & Career Preparation |
| Combining ML & DL SkillsMajor Project & Career Preparation | Covered in Python & Programming Foundation | Covered in Data Analytics, SQL & Power BI | Covered in Machine Learning | Covered in Deep Learning & Neural Networks | Covered in Applied Deep Learning & Model Deployment | Covered in Major Project & Career Preparation |
The full programme runs 6 Months. Where you finish is a question of pace rather than of syllabus — everyone covers all of it.
The case for it
A deep learning course is worth the time you give it only if you finish with trained models you can show and code you can defend.
You start with Python syntax and data structures, then move to NumPy, Pandas and exploratory data analysis, so your neural networks are built on clean, well-understood data.
You train, tune and validate models like regression, random forests and SVMs, giving you the baseline to know when a neural network is actually the right tool.
You build artificial neural networks, CNNs for images, and RNNs for sequence tasks, evaluating each model on real datasets.
You learn Streamlit, Flask to put models behind working interfaces, and finish with an end-to-end deep learning project for your portfolio.
Why this course
Six things we hold ourselves to for every Deep Learning batch that starts in Ludhiana.
every module ends in a deliverable, so you leave with reviewed work, not just notes.
you build and evaluate models on real datasets in scikit-learn, TensorFlow and Keras.
batches are small enough that a mentor reviews your project before you progress.
you learn Streamlit, Flask and Django to put models behind a working interface.
a single end-to-end deep learning project you can walk an interviewer through.
resume, portfolio and interview practice grounded in your own projects.
Why TechCadd
Techcadd's Deep Learning Course is built around deliverables and mentor review rather than lectures and a final certificate.
the people reviewing your work are applying these tools, not just teaching them.
individual review is possible because batches are kept small.
every module ends in something you built and can show, from month one.
you work on genuine data, including messy data that needs cleaning, not sanitized samples.
you learn Streamlit, Flask and Django so your models run as applications, which most courses skip.
Who can join
This programme fits anyone starting from a non-AI background who is willing to build the programming and data foundations first.
you start with Python from zero, so no prior coding is assumed, and you build toward a portfolio project by month six.
weekend batches let you keep your job while adding deep learning to a technical or analytics role.
if you come from IT support, testing, or a non-technical job, the structured month-by-month progression gives you a checkable deliverable at every stage rather than one final exam.
you learn to build and read models on real datasets, which is enough to scope AI work for your own company or evaluate a vendor's claims.
Not sure which of these you are, or whether the timing works around what you already do? That is exactly what the call is for. Ask about Deep Learning
Technology ecosystem
Deep Learning is the centre. These are the tools you use around it in a working team.
Hands-on projects
Each one lands in your portfolio with the working files, the process and something a reviewer can open.
Certification
Finish the Deep Learning programme at techcadd Ludhiana and you leave with more than a line on a CV — a verifiable certificate, and the project work that makes it mean something in an interview.
Issued in your name on completion of the Deep Learning syllabus, with a reference number an employer can verify with us.
A separate certificate for the capstone you submit, naming the project so the work is attached to the credential.
Students who complete the live-project phase receive an internship letter covering the duration and the work delivered.
Every file, repository and deployed link stays yours — the part of the credential a reviewer can actually open.
techcadd has been training in Ludhiana since 2007. The certificate carries that record; the Deep Learning work you did carries the rest.
Where it takes you
The route from your first module to the roles Deep Learning opens — and the work that has to exist at each step.
employers check whether you can train, tune and validate a model, and explain why you chose it.
they look for a working neural network project and your understanding of when a CNN or RNN is the right choice.
they check your ability to clean and explore a dataset and report findings clearly.
they check whether you can deploy a model behind a working interface, not just in a notebook.
they check SQL, Python and visualization skills alongside basic model literacy.
Salary outlook
Indicative ranges for the roles this course opens — what a fresher out of Ludhiana is offered, what the metro and remote markets pay for the same skills, and how that moves with two or three years of work behind you.
| Role | Ludhiana & Punjab | Delhi NCR & Bengaluru | Remote & freelance |
|---|---|---|---|
| Machine Learning EngineerEntry | ₹2.4–4.2 LPA | ₹4–8 LPA | ₹20k–45k / project |
| Deep Learning Engineer Entry to mid | ₹3.6–6.5 LPA | ₹6.5–14 LPA | ₹35k–90k / project |
| Data ScientistEntry to mid | ₹3.6–6.5 LPA | ₹6.5–14 LPA | ₹35k–90k / project |
| AI Application DeveloperMid | ₹3.6–6.5 LPA | ₹6.5–14 LPA | ₹35k–90k / project |
Ranges are indicative, drawn from what our own students report and from openings we see through the placement cell. Actual offers depend on your portfolio, the interview and the company — nobody can promise you a number, and we do not.
Machine Learning Engineer, Deep Learning Engineer , Data Scientist, AI Application Developer and related positions, depending on which part of the syllabus you go deepest on.
The first jump usually comes at 18–24 months, once you have shipped work you can point to. Depth in one area moves it faster than breadth across many.
Yes, and a good number of our students do. Remote and contract work is the reason Ludhiana candidates now compete for the same briefs as metro ones — the portfolio travels, the address does not matter.
IT services, manufacturing and export units running automation, e-commerce and D2C brands, healthcare, education, and the agencies serving all of them. Punjab hiring is broader than it looks from a job board.
It helps with the practical half. The projects and tooling carry into an M.Tech, MCA or a specialisation abroad, and the portfolio is often what separates two applicants with the same marks.
Future scope
The skill does not stand still, and neither does what it is worth. Here is how your career grows as you move from fresher to specialist.
Entry roles such as Machine Learning Engineer open as soon as you have projects that run. At this stage nobody is asking about your marks — they are asking you to walk through something you built.
The generalists plateau; the specialists do not. Depth in one part of Deep Learning — the part your first job leans on hardest — is what moves you towards deep learning engineer work.
Architecture, standards, hiring and mentoring. The technical skill is assumed by now; what you are paid for is judgement, and judgement only comes from having shipped things that mattered.
Teams expect Deep Learning work to be done alongside AI tooling. It raises the floor on output and raises the bar on what counts as a junior — which is exactly why the fundamentals in this course are taught the hard way.
What used to be one narrow role now touches data, deployment and the product decision behind it. Every extra layer of Deep Learning you understand is another kind of room you get invited into.
Remote and hybrid hiring means Ludhiana, Jalandhar and Chandigarh candidates now compete for the same roles as Bengaluru ones. Location has stopped being the ceiling it used to be.
Hiring has moved to portfolios, take-home tasks and live problem solving. A certificate opens a shortlist; work that runs is what gets you through the round after it.
Hiring across
The comparison
This comparison covers the differences that actually affect what you can show an employer at the end.
| What to ask about | techcadd | Typical institute |
|---|---|---|
| Live project work | Every module, from month one | Often only at the end, if at all |
| Mentor review | Individual review of your deliverable | Group feedback or none |
| Batch size | Kept small for review to be possible | Large lecture-style batches |
| Deployment | Streamlit, Flask taught | Often omitted entirely |
| Curriculum depth | Python → ML → deep learning → deployment | Often jumps straight to tools |
Written about the market, not about any particular institute in it. Visit two or three, sit through a demo class at each, and ask all eight of these questions — that is the only version of this table worth trusting.
Student Voices
Feedback from students who completed the Deep Learning programme at techcadd Ludhiana.
Simranjeet Kaur
Deep Learning / B.Sc. IT graduate
I joined with no background in this. By the third month I was building Deep Learning work on my own, and the project reviews are where I actually learnt to do it properly.
Harman Sethi
Deep Learning / Now working as an intern in the field
The classes are practical. Every session ends with a task that has to work, so you cannot fake understanding. That habit helped me most in interviews.
Ankit Verma
Deep Learning / BCA final year
Doubt support was the difference for me. My trainer sat with my work, found the mistake and made me fix it myself instead of handing over the answer.
Navjot Singh
Deep Learning / Career switch from operations
I came for the skill and left with a portfolio — projects I could actually demo on a call, not a certificate I had to explain.
Simranjeet Kaur
Deep Learning / B.Sc. IT graduate
I joined with no background in this. By the third month I was building Deep Learning work on my own, and the project reviews are where I actually learnt to do it properly.
Harman Sethi
Deep Learning / Now working as an intern in the field
The classes are practical. Every session ends with a task that has to work, so you cannot fake understanding. That habit helped me most in interviews.
Ankit Verma
Deep Learning / BCA final year
Doubt support was the difference for me. My trainer sat with my work, found the mistake and made me fix it myself instead of handing over the answer.
Navjot Singh
Deep Learning / Career switch from operations
I came for the skill and left with a portfolio — projects I could actually demo on a call, not a certificate I had to explain.
Simranjeet Kaur
Deep Learning / B.Sc. IT graduate
I joined with no background in this. By the third month I was building Deep Learning work on my own, and the project reviews are where I actually learnt to do it properly.
Harman Sethi
Deep Learning / Now working as an intern in the field
The classes are practical. Every session ends with a task that has to work, so you cannot fake understanding. That habit helped me most in interviews.
Ankit Verma
Deep Learning / BCA final year
Doubt support was the difference for me. My trainer sat with my work, found the mistake and made me fix it myself instead of handing over the answer.
Navjot Singh
Deep Learning / Career switch from operations
I came for the skill and left with a portfolio — projects I could actually demo on a call, not a certificate I had to explain.
Real, unedited feedback from techcadd learners on Google.
Frequently asked questions
The 7 things people ask most often about the Deep Learning course at techcadd Ludhiana.
The complete Deep Learning programme runs for 6 Months depending on the batch you choose. Weekday, weekend and fast-track options are available, along with shorter modules for students who only need the fundamentals.
School students after 12th, college students from any stream, graduates and working professionals changing track. The first module assumes no prior experience.
No. The course starts from the basics. If you already have some background, your trainer will move you faster through the first module so you reach the project work sooner.
Python, Numpy, Pandas, Matplotlib, Seaborn, Scikit-learn, Tensorflow, Streamlit, Flask, SQL and Power BI — plus the day-to-day tooling and workflow that surrounds them in a real team.
Yes. Each module closes with a lab project, and the course ends with a capstone you can put on your portfolio and defend in an interview.
Placement support includes resume and portfolio review, aptitude and role-specific practice, mock interviews and interview referrals through our hiring network.
Yes. You receive a techcadd Deep Learning completion certificate, and a separate project certificate for the capstone you submit.
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