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Data Science with Python Track

Our Data Science course is a comprehensive training program designed to equip participants with the essential skills and knowledge to excel in the field of data science. Through a series of structured levels, participants will learn programming fundamentals, statistical analysis techniques, data wrangling strategies, data visualization principles, and machine learning algorithms, and apply their skills in a real-world data science project. With flexible scheduling options, expert instructors, and hands-on learning, our course provides a solid foundation for individuals seeking to enter or advance their careers in the exciting and rapidly growing field of data science.


No specific prerequisites in terms of prior education or professional experience.

Suitable for recent graduates, working professionals, and people looking to get into the data science field.


Sunday & Saturday:

9 am - 1 pm

We provide flexible timing options to cater to the needs of our diverse student base.


$1000 per level

20% off if the student enrolls for the full track.


Our comprehensive data science program is designed to equip you with the essential skills and knowledge to excel in the field of data science. The program includes the following Levels and subcourses:

Level 1 

Introduction to Programming  (6 sessions)
  • Programming Fundamentals

  • Data Types and Structures

  • Object-Oriented Programming

  • Input and Output

  • Control Structures

  • Debugging and Error Handling

Level 2

Statistics and Probability  (8 sessions)
  • Descriptive Statistics

  • Probability Theory

  • Statistical Inference

  • Linear Regression

  • Statistical Software

  • Data Sampling and Experimental Design

Level 3

Data Wrangling  (6 sessions)
  • Data Acquisition

  • Data Cleaning

  • Data Transformation

  • Data Manipulation

  • Data Integration

Level 4

Data Visualization (4 sessions)
  • Data Visualization

  • Fundamentals Exploratory

  • Data Analysis

  • Data Storytelling

  • Visualization Tools

  • Visualization Ethics

  • Visualization Implementation

Level 5

Machine Learning  (8 sessions)
  • Supervised Learning

  • Unsupervised Learning

  • Neural Networks

  • Model Selection and Evaluation

  • Deep Learning

  • Real-world Applications

Level 6

Data Science Project  (4 sessions)
  • Apply the learned concepts and techniques
    in a comprehensive data science project


Join our data science track and acquire the skills and knowledge necessary to excel in the dynamic field of data science.

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