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Data & AI Training

Data Science

Learn the complete data science workflow: Python, statistics, data wrangling, visualisation, machine learning models, evaluation and communication.

IntermediateAI & Data

At a glance

  • CategoryData & AI Training
  • LevelIntermediate
  • Curriculum6 modules, 4 project ideas
  • InstituteAIIT Roorkee, Roorkee

Course Overview

About this course

Data science combines programming, statistics and domain understanding to extract insight and build predictive models. It sits at the centre of modern analytics and AI work.

This course takes you through the full workflow using Python: collecting and cleaning data, exploratory analysis, statistics and hypothesis testing, feature engineering, supervised and unsupervised machine learning, model evaluation and communicating results responsibly.

Learning Objectives

By the end of Data Science, learners should be able to:

  • Wrangle and explore datasets with pandas and NumPy
  • Apply statistics and hypothesis testing to real questions
  • Engineer features and build machine learning models with scikit-learn
  • Evaluate models with appropriate metrics and validation
  • Communicate results and limitations clearly

Topics Covered

01Python for data science
  • NumPy and pandas
  • Jupyter workflow
  • Data collection from files and APIs
02Exploratory data analysis
  • Cleaning and missing values
  • Visualisation with Matplotlib and Seaborn
  • Finding patterns
03Statistics
  • Probability and distributions
  • Confidence intervals
  • Hypothesis testing and correlation
04Machine learning
  • Regression and classification
  • Decision trees and ensembles
  • Clustering
05Model quality
  • Feature engineering
  • Cross validation
  • Metrics, bias and overfitting
06Communication and deployment
  • Reports and dashboards
  • Simple model APIs
  • Ethics and responsible data use

Topic order and depth may be adjusted for the batch, format and learner level.

Practical Learning

Every module pairs explanation with hands-on work. Typical practical activities in this course:

End-to-end notebooks on public datasets

Statistics exercises with real data

Model comparison challenges

Peer review of analysis notebooks

Representative Projects

Projects are chosen with mentors based on your level and interests. Examples include:

  • House price prediction model
  • Customer churn classification
  • Customer segmentation with clustering
  • Capstone data science report with presentation

Who Should Join

  • Graduates with a quantitative background
  • Python learners ready for data work
  • Engineering and science students
  • Analysts moving into predictive modelling

Prerequisites

  • Python basics
  • School level mathematics and willingness to learn statistics

Learning Format

This course can be offered in the following formats, depending on the batch:

  • Short-Term Courses
  • Long-Term Courses
  • Certification-Oriented Programs
  • Weekend Programs
  • Workshops
  • Live Project Training
  • Internship Programs

Ask the team for current batch timings and the formats open for Data Science.

Career Relevance

Skills from this course are relevant to roles and directions such as:

  • Data Scientist
  • Data Analyst
  • Machine Learning Engineer foundation
  • Research Assistant (data)

Career relevance describes where these skills are commonly used. It is not a promise of employment. Learners can use AIIT Roorkee's placement assistance for career preparation support.

FAQs

How much mathematics is needed for Data Science?

You need school level algebra and a willingness to learn statistics and probability. The course explains the mathematics behind methods in practical terms.

Does Data Science include machine learning?

Yes. Core machine learning methods are included. The Machine Learning course goes deeper into algorithms, tuning and deployment.

Can I join without Python?

Python basics are recommended. If you are new to programming, Python Training is a good first step.

What is the duration and schedule of this course?

Duration, batch timings and format are shared when you enquire, because they depend on whether you choose a short-term, long-term, weekend or training format. Contact the team by phone, WhatsApp or email for current batches.

Is placement assistance available?

Learners can use AIIT Roorkee's placement assistance, which includes career counselling, CV preparation, LinkedIn development, interview preparation and mock interviews. Placement assistance is career preparation support and does not constitute a guarantee of employment or placement.

Practical Lab Environment

Data Science Developer Console

Start Learning Data Science

Build practical engineering skills with 1-on-1 mentorship and live projects at AIIT Roorkee.

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