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LIVE TRAINING · MENTOR-LED PROJECTS

📊 Data Science & Machine Learning

Move from data analysis to predictive modelling, ML pipelines and model deployment.

⏱ 14 weeks Live Online • Small batch
Discuss dates & fees ↗View syllabus ↓
DATA & AI LABIllustrative workflow
01020304
Inspect the dataset and define a measurable question.
Explore each step

EXAMPLE PROJECT BRIEF

A reproducible analysis or model experiment

Use this example to discuss the project scope for this specialist module with your mentor.

What to demonstrate: Explain the baseline, avoid data leakage, and communicate limitations alongside the results.

What will you learn in Data Science & Machine Learning?

Working professionals with data or analytics backgrounds use this course to move into data-science and ML-engineering roles. The focus is on solving business problems with models that can be deployed and maintained.

What you will learn

  • Exploratory analysis and feature engineering
  • Supervised and unsupervised learning
  • Model selection, tuning and validation
  • ML pipelines and experiment tracking
  • Deploying models as APIs
  • Monitoring and retraining in production

✓ Job-Ready Track

This course is part of our job-ready track. It opens roles such as Data Scientist, ML Engineer, Applied Scientist. Placement assistance and weekly interview preparation are included.

Tools & technologies

🐍Python📊Pandas📈Scikit-learn🔥TensorFlow🧰MLflow⚡FastAPI🐳Docker☁️AWS

Syllabus

  • Business problem translation
  • Data cleaning and validation
  • EDA and visualisation
  • Feature engineering basics
  • Regression and classification
  • Model evaluation metrics
  • Cross-validation
  • Hyperparameter tuning
  • Clustering and dimensionality reduction
  • Tree-based models
  • Ensemble methods
  • Model interpretability
  • Pipelines with scikit-learn
  • Experiment tracking
  • Model packaging
  • API deployment
  • Neural networks with Keras
  • CNNs and transfer learning
  • NLP basics
  • When to use deep learning
  • Monitoring and drift detection
  • Retraining strategies
  • Capstone project
  • Interview preparation
Keep exploring

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Learn together & save

YOU + FOUR FRIENDS

Join with friends and save on fees.

Bring four friends or colleagues and ask about BAIC’s reduced fee for a group of five learners.

We’ll confirm your course’s eligibility, group fee, schedule and final payable amount before you enrol.

Ask about the group fee ↗
View Syllabus

Have questions about this programme?

Book a free introductory call. We will discuss your background, the syllabus and whether this is the right starting point.

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Data Science & Machine Learning course questions

What is the Data Science & Machine Learning course fee?

Ask a course advisor for the current batch fee, payment details and what is included before enrolling.

How long is the Data Science & Machine Learning course?

The published course duration is 14 weeks. Confirm the weekly timetable and hands-on work with your course advisor.

What will I learn in Data Science & Machine Learning?

Working professionals with data or analytics backgrounds use this course to move into data-science and ML-engineering roles. The focus is on solving business problems with models that can be deployed and maintained.

Your lead mentor

Gaurav S — Lead FDE, working with multinational clients (15 years of IT experience; previously at HCL, Accenture, HP and Wipro)

Ask about project feedback, the teaching approach and the support available for your course.

View Gaurav’s profile →