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Data & AI

Data Science

Statistics, Python and modelling, plus the storytelling that sells the result.

Five months across the data science workflow: framing a question, cleaning the data, modelling it honestly and presenting a result someone will act on.

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Data Science training at TechCadd
Certificate on completion
Category
Data & AI
Level
Beginner to Advanced
Duration
5 Months
Mode
Online / Offline
Data Science introductionIntroduction video coming soon
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Watch Course Introduction

Inside the Data Science track.

A short walkthrough of the syllabus, the projects you will build and how the batches are run — worth five minutes before you enrol.

Audience

Who can do this course?

The programme is built to work for people arriving from very different starting points.

  • Beginners

    No prior experience needed — the first modules start from fundamentals.

  • College students

    Fits alongside a degree, with weekend and evening batches covering the same syllabus.

  • Freshers

    Build the portfolio and interview practice that a first role actually asks for.

  • Working professionals

    Weekend batches and 1-on-1 mentoring for people training without taking leave.

  • Career switchers

    A structured route in from another field, with guidance on how to position the move.

Why this program

Why choose this program?

Six things that separate a programme you finish from one you benefit from.

  • 01

    Industry-oriented curriculum

    Built backwards from live job descriptions and rewritten as the stack moves.

  • 02

    Hands-on from day one

    You spend more time building than watching. Every concept lands in working code.

  • 03

    Mentor guidance

    Small batches, direct access to your trainer, and reviews on the work you produce.

  • 04

    Real-world tools

    The same editors, version control and deployment tooling teams use in production.

  • 05

    Interview preparation

    Mock rounds, portfolio review and the questions this particular role gets asked.

  • 06

    Career-focused outcome

    The programme ends with work you can show and a plan for the roles you are targeting.

Curriculum

Course modules

4 modules, 64 sessions — sequenced so each one builds on what you just shipped.

  • 4 Modules
  • 5 Months
  • Beginner to Advanced
  • Certificate Included
  1. Beginner
  2. 4 Modules
  3. Advanced
  4. Projects
  5. Certification

  1. What this module covers

    • Python
    • Pandas
    • NumPy
    • Notebooks
    16 sessions
Outcomes

What you will learn

Concrete capabilities, not topics covered. Each one is demonstrated in work you keep.

  • Frame a business question as a data problem
  • Clean and reshape messy datasets
  • Apply statistics without over-claiming
  • Build and validate predictive models
  • Present findings so a decision follows
Toolchain

Tools & technologies you'll learn

The same tooling the teams hiring for this role use every day.

  • Python
  • Pandas
  • NumPy
  • scikit-learn
  • Matplotlib
  • SQL
  • Jupyter
  • Power BI
After the course

Career outcomes

After completing Data Science, these are the directions students most often take. Outcomes depend on your own work and the market — we do not promise placements or salaries.

Job roles to target

  • Data Scientist
  • Data Analyst
  • Research Analyst
  • Analytics Consultant

Where the work is

  • Product and agency teams
  • Freelance projects
  • Campus placements
  • In-house roles

Where to go next

  • Machine Learning
  • Artificial Intelligence
  • Data Analytics
  • Cloud & DevOps

Industry applications

  • Finance
  • Healthcare
  • Retail
  • Consulting
Practice

Hands-on projects

Every module ends in built work. These are the pieces you finish the programme holding.

  • End-to-end analysis

    End-to-end analysis

    Advanced

    One question taken from raw data to a presented recommendation.

    • Python
    • Pandas

    Skills practised: Framing, Analysis, Presenting

  • Predictive model

    Predictive model

    Intermediate

    A validated model with explained drivers.

    • scikit-learn

    Skills practised: Modelling, Validation, Explainability

Explore Projects
A TechCadd trainer running a session
1000+Students TrainedLive ProjectsPlacement Support
  • 0+Happy Students
  • 0+Industry Projects
  • 0%Practical Training
  • YesIndustry Experts
Teaching

Why learn with us?

Every trainer here still ships production code. That is the whole basis of the teaching: answers come from current practice rather than from a slide deck written three years ago.

  • Practitioners, not presenters

    Sessions are run by engineers working on live systems, so the examples come from real codebases.

  • Project-based from week one

    You build as you learn. Each module ends in something that runs, not in a quiz.

  • Personalised guidance

    Small batches mean your mentor knows what you are stuck on and what you are aiming at.

  • Doubt support that continues

    Doubt sessions and mentor hours carry on after the certificate is printed.

Questions

Frequently asked questions

The questions counsellors are asked most about Data Science.

  • Yes. Data Science begins from fundamentals, and the pace is set so nothing is assumed.

Course enquiry

Ask About Data Science

Send your question and a counsellor will call you back. No obligation to enrol.

  • Live Project Training
  • Internship Certificate
  • Placement Assistance
  • Industry Mentors
  • Interview Preparation
  • Online + Offline Mode

5 Months · Online / Offline

  • 100% Free Counselling
  • No Spam Calls
  • Career Guidance Included

We use your number only to answer this enquiry.

Ready to start your learning journey?

Build practical skills, work on real projects and take the next step towards your career.

Enroll in Data ScienceTalk to an Expert
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