Flagship project
Exploratory Analysis
A full EDA notebook on a real dataset with cleaned data and visual findings.
- pandas
- scikit-learn
- TensorFlow
Internship & Training · Short Term · techcadd Amritsar
45 Days / 6 Weeks Data Science Training in Amritsar
45 Days / 6 Weeks Data Science Training in AmritsarSix weeks to go from Python basics to one trained and deployed ML model. Data Science summer training and 6 weeks industrial training in Amritsar, with a live project, daily mentor review and an internship certificate.
45 days · 6 weeksLive client briefClassroom & live online
Programme at a glance
- Duration
- 45 days · 6 weeks
- Level
- Beginner to project-ready
- Mode
- Classroom & live online
- Open to
- 12th pass, B.Tech, BCA, MCA, diploma students, graduates and working professionals
- Batches
- Weekday, evening, weekend & 1-on-1
- You leave with
- Certificate + internship letter
45 days
Duration
6
Structured blocks
3
Live projects
Included
Internship letter
Pick your format
Have a full semester? 6 months Data Science training
Ways to take 45 Days / 6 Weeks Data Science Training trainingWith a 6 months internship or training semester, the complete Data Science track goes deeper — more live briefs, a capstone project and placement prep.
6 Months Data Science Training
6 months · training semester
The full data science track over six months, including deep learning and a capstone project you can demo.
- Supervised, unsupervised and deep learning
- Client prediction project
- Capstone, report + internship letter
Data Science Training — compare formats
45 days – 6 months
Python, statistics and machine learning, ending in a deployed model on real data.
- Python & ML
- Real datasets
- Deployed model
Course Overview
techcadd's 45 Days / 6 Weeks 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.
The terms
What 45 Days / 6 Weeks Data Science Training actually involves
Need 45 days or 6 weeks Data Science training for your summer break or your college's 6 weeks industrial training? It's the same programme, built for exactly that slot. 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.
Students from Amritsar and nearby towns join this 45 days / 6 weeks Data Science internship to learn what college skips: Python for Data Science, Statistics & Probability and Exploratory Data Analysis, plus 3 more blocks, worked on Python 3, NumPy, pandas and scikit-learn — the tools our trainers use on real client work. Batches stay at 15 – 20 students, so your trainer reviews your work every day.
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.
Programme factsConfirmed in writing at counselling
- Duration
- 45 days · 6 weeks
- Level
- Beginner to project-ready
- Mode
- Classroom & live online
- Open to
- 12th pass, B.Tech, BCA, MCA, diploma students, graduates and working professionals
- Batches
- Weekday, evening, weekend & 1-on-1
- You leave with
- Certificate + internship letter
- 45 days / 6 weeks — a summer break or your college's training slot
- Python, pandas and EDA
- scikit-learn model with Streamlit demo
- Training report in your department's format
Why now
45 Days / 6 Weeks Data Science Training is powering the next generation of industry leaders
45 Days / 6 Weeks Data Science Training is powering the next generation of industry leaders- 45 days / 6 weeks — a summer break or your college's training slot
- Python, pandas and EDA
Reviewed by mentors · built for interviews
Live client work from week one, at the Amritsar lab.
Where the 45 days · 6 weeks goes
The calendar, spelled out before you enrol
45 Days / 6 Weeks Data Science Training scheduleNo block is padding and none of it is a lecture series. Each span below ends in something a trainer has signed off on.
- Weeks 1 – 2Step 01 of 03
Foundations & toolchain
Python, NumPy and pandas, then statistics and exploratory analysis on real datasets, worked daily with a trainer reviewing your notebooks.
- Weeks 3 – 4Step 02 of 03
The live brief
A real prediction brief: features engineered, models trained and evaluated with scikit-learn, and the best one tuned, reviewed in daily increments.
- Weeks 5 – 6Step 03 of 03
Report, certificate & interview prep
The model deployed with Streamlit, a project write-up, then the certificate, the letter and a mock data-science interview.
Module by module
The curriculum, module by module
Module by module curriculum6 modules, each ending in something reviewable that goes into your portfolio.
- Module 01 of 06
Python for Data Science
Python for Data Science is where the 45 Days / 6 Weeks 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.
Topics covered
- NumPy arrays
- pandas DataFrames
- Jupyter workflow
Tools in this module
Python 3NumPypandasscikit-learnYou finish withA reviewed piece of work demonstrating numpy arrays and pandas dataframes.
- Module 02 of 06
Statistics & Probability
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.
Topics covered
- Distributions
- Hypothesis testing
- Sampling
Tools in this module
pandasscikit-learnTensorFlowJupyterYou finish withA reviewed piece of work demonstrating distributions and hypothesis testing.
- Module 03 of 06
Exploratory Data Analysis
By the end of exploratory data analysis, you can make the calls a working 45 days / 6 weeks data science training practitioner makes daily — and explain why you made them.
Topics covered
- Cleaning and outliers
- Visualisation
- Feature engineering
Tools in this module
TensorFlowJupyterStreamlitGitYou finish withA reviewed piece of work demonstrating cleaning and outliers and visualisation.
- Module 04 of 06
Machine Learning
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.
Topics covered
- Regression and classification
- Clustering
- Model evaluation
Tools in this module
StreamlitGitPython 3NumPyYou finish withA reviewed piece of work demonstrating regression and classification and clustering.
- Module 05 of 06
Deep Learning Basics
Everything in deep learning basics feeds the next stage of the 45 days / 6 weeks data science training build, so nothing here is theory you park and forget.
Topics covered
- Neural networks
- TensorFlow intro
- Image and text data
Tools in this module
Python 3NumPypandasscikit-learnYou finish withA reviewed piece of work demonstrating neural networks and tensorflow intro.
- Module 06 of 06
Model Deployment
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.
Topics covered
- Saving models
- Streamlit apps
- Presenting results
Tools in this module
pandasscikit-learnTensorFlowJupyterYou finish withA deployed model with its notebook and evaluation.
Eligibility
Four kinds of people join this batch. You are probably one of them.
Who this course is forThere is no entrance test and no prerequisite degree. What the programme does assume is that you will show up for the full 45 days · 6 weeks and do the project work.
01No experience needed
Students after 12th
Nothing is assumed beyond a 12th pass and comfort with a computer. 45 Days / 6 Weeks 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.
02Counts for college
Graduates & final-year students
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.
03Evening & weekend
Working professionals
Two-hour classes either side of a working day, or a weekend batch across 45 days · 6 weeks. You are not asked to resign to retrain, and the project work is scheduled around the batch you pick.
04Immediately usable
Freelancers & business owners
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.
05Gap explained
Career restarters
A gap on a CV is only a problem if there is nothing to put in it. 3 reviewed projects and a documented letter turn 45 days · 6 weeks into an answer rather than a question.
06Fills the gaps
Self-taught learners
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.
Where it leads
The roles this portfolio opens
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.
Certification
Get Certified in45 Days / 6 Weeks Data Science Training
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.
Future scope
Where 45 days / 6 weeks data science training is headed from here
Where 45 days / 6 weeks data science training is headed from hereA certificate answers what you can do today. This is the honest answer to what 45 days / 6 weeks 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.
- Demand is structural, not seasonalEmployers keep filtering for candidates who have already done real, supervised delivery work, not just coursework — a documented internship is what turns a resume into a shortlist.
- The skill ladder keeps climbingJunior Data Scientist is the entry rung, not the ceiling. Once that portfolio is in place, machine learning trainee is the realistic next step — a promotion earned on the job, not a second course you have to go back and pay for.
- Tooling changes; fundamentals compoundPython 3 and the rest of the stack will look different in five years — they always do. What does not expire is the fundamentals this course is built around, which is why the syllabus is reviewed each intake instead of frozen once and reused.
- Remote and hybrid widen the marketA 45 days / 6 weeks data science training portfolio built in Amritsar competes for the same remote and hybrid roles as anywhere else. Companies hiring for this work are increasingly indifferent to which city the offer letter is posted to.
The 45 days · 6 weeks 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.
What you build
Projects that answer the interview question for you
Portfolio projectsEach project is reviewed individually, and the review notes go into your portfolio documentation.
Price Prediction Model
A regression model with feature engineering and a clear evaluation.
- TensorFlow
- Jupyter
- Streamlit
Live Prediction Brief
A real problem from the techcadd client pipeline, solved with a trained model.
- Streamlit
- Git
- Python 3
The working loop
Learn it. Build it. Make it yours.
Learn it. Build it. Make it yours.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.
- 01
Understand
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
- 02
Build
Work hands-on with trainer feedback arriving while the decisions are still cheap to change.
Price Prediction Model
- 03
Present
Turn the finished work into a portfolio story you can defend line by line in an interview.
Live Prediction Brief
Why techcadd
Why students choose techcadd
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 45 Days / 6 Weeks Data Science Training runs on exactly that model.
Trainers who still do the work
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.
Live projects, real consequences
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.
Small batches and open lab hours
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.
Internship letter and certificate
Every student finishes with an industry-recognised certificate and a documented internship on real work, accepted for university industrial training requirements.
A placement cell that persists
Mock interviews, CV reviews and drives with hiring partners across Amritsar and Punjab — repeated after a rejection, not abandoned.
Since 2007, 15,000+ students
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.
Student reviews
What the last few batches actually said
45 Days / 6 Weeks Data Science Training course reviewsCollected from students who completed the 45 days / 6 weeks 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
181 verified reviews from Amritsar students
- 5★
- 85%
- 4★
- 7%
- 3★
- 5%
- 2★
- 2%
- 1★
- 1%
I joined the 45 Days / 6 Weeks 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 45 days · 6 weeks. Anything I missed got re-explained without fuss, and lab access outside batch hours was never a problem.
pandas 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 45 days / 6 weeks 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 NumPy rather than the older tooling most 45 days / 6 weeks 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 3 projects I can demo, not just a certificate.
Questions we get asked at the admissions desk
Frequently asked questionsIf something here is not covered, the Amritsar desk will answer it directly — no call-back queue.
Yes. 45 days is about six weeks, so it's one programme: six weeks to go from Python basics to one trained and deployed ML model. It fits a summer or winter vacation and the 6 weeks industrial training most colleges ask for.
Get started today
Not sure if 45 Days / 6 Weeks Data Science Training is the right fit?
One call with a counsellor is usually enough to find out. Book a free demo class and see the Amritsar lab before you decide.
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Course Information
Ask about 45 Days / 6 Weeks Data Science Training
Enquire about the 45 Days / 6 Weeks Data Science Training courseSend your question and a counsellor will call you back about batch timings, fees, EMI options, placement record, or whether this course fits your background.
- Free career counselling
- No registration fee
- Placement support included
