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Data Science

Python, statistics, SQL and visualisation: collect, clean and analyse data to answer real questions.

5 Months Classroom & Online Intermediate Course completion certificate
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About this course

Learn Data Science with Python, SQL, Statistics, Pandas, NumPy, Visualization and Machine Learning at Laaksh Institute in Rohini, Delhi. Classroom & online training.

Who is this course for?

  • Students and freshers who want a job-ready skill
  • Working professionals looking to upgrade
  • Anyone who wants to learn by doing, not just by listening

Eligibility: Graduate or working professional.

Data Science Course

Learn how to turn raw data into meaningful insights with practical Data Science training at Laaksh Institute. This course covers the essential skills required to collect, clean, analyse and visualize data using Python, Statistics, SQL and Data Visualization.

Designed for students, freshers and working professionals, the course focuses on practical learning through projects, lab practice and real-world data problems.

About Data Science Course

The Data Science Course in Rohini, Delhi is designed to help learners build a strong foundation in data analysis and machine learning. You will learn how to work with datasets, identify patterns, create meaningful visualizations and use basic machine learning techniques to solve data-driven problems.

The course combines classroom learning with practical exercises so that students can understand concepts and apply them to real projects.

What You Will Learn

  • Python for Data Science

  • NumPy and Pandas

  • Data Cleaning and Data Manipulation

  • Statistics and Probability

  • SQL and Database Queries

  • Data Visualization with Matplotlib

  • Exploratory Data Analysis

  • Introduction to Machine Learning

  • Model Evaluation

  • Data Analysis and Reporting

  • Capstone Project

Data Science Course Syllabus

1. Python for Data Science

Learn Python fundamentals required for working with data, along with essential libraries such as NumPy and Pandas.

2. Statistics & SQL

Understand descriptive statistics, probability basics and SQL queries. Learn how to work with databases, filter data and perform SQL joins.

3. Data Visualization & Modelling

Create meaningful charts using Matplotlib and learn the fundamentals of machine learning, including basic model evaluation techniques.

4. Capstone Project

Apply your learning to a practical project. Work on a problem statement, perform data analysis, prepare a report and present your findings.

Who Can Join This Course?

This course is suitable for:

  • Students and freshers looking to develop job-ready skills

  • Graduates interested in Data Science

  • Working professionals looking to upgrade their technical skills

  • Learners who want practical experience with data analysis

  • Anyone interested in Python, analytics and machine learning

Why Learn Data Science at Laaksh?

At Laaksh Institute, students get more than classroom-based learning. The course includes live-project training, unlimited lab practice, industry-expert trainers and a course completion certificate. Students can also attend a free demo class before joining the course.

Course Highlights

Duration: 5 Months
Mode: Classroom & Online
Level: Intermediate
Training: Practical & Project-Based
Certificate: Yes
Lab Practice: Unlimited after class
Demo Class: Free

Build Practical Data Science Skills

Data Science is used across businesses to understand information, identify trends and support data-driven decisions. By learning Python, SQL, statistics, visualization and machine learning fundamentals, students can build a strong foundation for further learning and professional development.

Start your Data Science journey with practical training at Laaksh Institute, Rohini, Delhi.

What you get

  • Live-project training
  • Unlimited lab practice after class
  • Industry-expert trainers
  • Certificate on completion
  • Free demo class before you join

Syllabus

  • Python essentials
  • NumPy and Pandas

  • Descriptive statistics
  • Probability basics
  • SQL queries and joins

  • Charts with Matplotlib
  • Intro to machine learning
  • Model evaluation

  • Problem statement
  • Analysis and report
  • Presentation

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