Data Science with AI/ML Course in Mohali: Online & Offline Batches

The Data Science with AI/ML course in Mohali at techcadd is offered in both online and offline batches, so you can learn Python, statistics, machine learning and AI fundamentals in the format that fits your routine. Both modes follow the same syllabus and project work, and this page explains how each batch type works so you can choose with confidence.

Online and Offline Batches at a Glance

Offline batches run in the techcadd Mohali classroom and lab, where you work on lab systems or your own laptop with a mentor in the room. Online batches use live, instructor-led sessions with screen sharing, so you code along in real time rather than watching pre-recorded videos only.

The topics, assignments and capstone expectations are the same in both modes. What changes is how you attend, how you ask doubts and how you collaborate with other learners.

• Offline: face-to-face teaching, lab practice and quick in-person doubt clearing.

• Online: live sessions from home, shared notebooks and doubt support over chat or call.

• Hybrid needs: if your schedule changes, ask the team whether switching between modes is possible.

Who Each Batch Mode Suits

Choose offline if

you live in or near Mohali, Chandigarh or Kharar, learn better with a fixed classroom routine, or want to pair-program with classmates on lab exercises.

Choose online if

you work during the day, live outside the Tricity, or prefer to study from home with a stable internet connection and a laptop that can run Python and Jupyter.

Data Science with AI/ML Syllabus

The syllabus builds from programming foundations to model building, and it is shared across both batch types.

Python for data work

Variables, functions, loops, list comprehensions, file handling and writing clean, reusable code in Jupyter Notebook and VS Code.

Data handling with NumPy and Pandas

Arrays, DataFrames, merging, grouping, handling missing values and preparing datasets for analysis.

Statistics and probability

Descriptive statistics, distributions, sampling, hypothesis testing and correlation, explained with real examples.

Visualisation and EDA

Matplotlib and Seaborn charts, exploratory data analysis and presenting findings clearly.

Machine learning with scikit-learn

Regression, classification, decision trees, random forests, clustering, train-test splits, cross-validation and evaluation metrics.

AI and deep learning foundations

Neural network basics with TensorFlow or Keras, an introduction to NLP and computer vision, and how large language model tools are used in data workflows.

How Practical Work Runs in Each Mode

In offline batches, mentors walk around the lab, review notebooks on screen and help you debug errors as they happen. In online batches, you share your screen or notebook link so the mentor can review your code live, and assignments are submitted through shared folders or Git repositories.

In both modes, you are expected to practise between sessions. Data science skills grow through repetition: cleaning messy data, trying different models and explaining why one performs better than another.

Projects and Portfolio

• A sales or retail dataset analysis with clear visual insights

• A house price or demand prediction model using regression

• A customer churn or loan approval classifier with evaluation metrics

• A text sentiment classifier as an introduction to NLP

• A capstone project documented on GitHub with a short write-up

Projects are designed so that both online and offline learners finish with a portfolio they can show in interviews.

Duration, Fees and Batch Timings

Batch timings, total duration and the fee structure can differ between online and offline modes and may change over time. Please contact the techcadd Mohali team for the current fee structure, upcoming batch start dates and available weekday or weekend slots.

When you enquire, mention your preferred mode, your current background and the hours you can commit each week so the team can suggest a suitable batch.

Skills and Career Direction

The course builds skills used in roles such as data analyst, junior data scientist, machine learning trainee and business intelligence associate. Outcomes depend on your effort, the quality of your projects and market conditions, so steady practice matters more than the mode you choose.

Why Learn Data Science at techcadd Mohali

• Same syllabus in both modes: online learners are not given a reduced course.

• Mentor-led practice: doubts are handled during and after sessions.

• Project focus: every module ends in hands-on work rather than theory only.

• Flexible choice: pick the format that suits your studies or job.

Frequently Asked Questions

Is the online batch the same as the offline batch?

Yes, both follow the same syllabus, assignments and project expectations. Only the delivery method differs.

Are online classes live or recorded?

Online batches are run as live instructor-led sessions. Ask the team whether recordings are shared for revision in your batch.

What do I need for the online batch?

A laptop or desktop that can run Python, Jupyter Notebook and a browser, plus a stable internet connection and a headset.

Can I switch from online to offline later?

Switching may be possible depending on batch availability. Please confirm this with the team before enrolling.

Do I need a coding background for Data Science with AI/ML?

No prior coding is required, as the course starts with Python basics. Comfort with school-level maths helps.

How do I know the current fee and timings?

Contact the techcadd Mohali team for the current fee structure, batch timings and start dates for each mode.

Enquire About Data Science with AI/ML Batches at techcadd

Tell us whether you prefer an online or offline batch and we will share the available options. Contact techcadd Mohali to ask about the next online or offline batch.