Year 10

Advance Concepts of Data Science

Advance yourself in Data Science technologies by gaining practical knowledge of all the Data Science libraries. Excel in making different types of predictive models and recognition models to solve real-life problems on your own.

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Data Analysis Tools and R Programming

Learn R programming for statistical computing, graphics, data analytics and scientific research.
Grab the knowledge by learning the techniques of deep learning tools - Keras.

R Programming

This section covers the overview of R programming. Learn the techniques of Visualization and Statistics through R programming language.

  • Introduction to R Programming
  • R Installation
  • Data Types and Data Structures
  • Variables and Operators
  • If-else and else if statements
  • R switch Statement
  • Next, Break and Other Statements
  • R Vectors and R Lists
  • Pirate Face
  • R Arrays and R Matrix
  • R Data Frame and R Factors
  • R Data Reshaping
  • Object Oriented Programming
  • R Debugging
  • R Data Interfaces
  • R Data Visualization
  • R Regression
  • R Statistics

Keras - Data Science Tools

This section covers the Keras Data Science tool and API's used for data sciences.

  • Introduction to Keras
  • Introduction to APIs
  • Functional API
  • Model API
  • Layer API
  • Callbacks API
  • Data Preprocessing & Optimizers
  • Woking with RNN
  • Keras Applications
  • Training Keras models with TensorFlow Cloud

Major Project

  • Statistics Project
  • Keras Application

Skill Benefit

  • Enhanced Mathematical skills with programming
  • Enhance Analytical skills

Learning Outcomes

  • Learn R Programming Language and the implementation of mathematic formulas of regression and statistics in the programs
  • Also, Grab knowledge of how to create APIs for Data science by using Keras Tool.


Data Mining and Tableau Tool

Create insightful and impactful visualizations in an interactive and colorful way by learning data visualization tool Tableau and SciKit.

Learn the data mining techniques and tools to analyse and extract the valuable information from the huge data.

SciKit - Data Science Tool

This section covers the Scikit Data Science Tool of Machine learning with deep understanding of Supervised and Unsupervised Learning.

  • Introduction to Scikit Learn
  • Introduction to ML using Scikit-Learn
  • ML the Problem Setting
  • Supervised Learning
  • Unsupervised Learning
  • Model Selection and Evaluation
  • Inspection
  • Dataset Transformation
  • Dataset Loading Utilities
  • Computing with Scikit Learn

Introduction to Data Mining

This section covers the overview of Data Mining and it's classifications. Students will develop the various projects on classifications using Data Mining techniques.

  • Introduction to Data Mining
  • Algorithms, Tasks and Issues
  • Terminologies, Knowledge Discovery and Query Language
  • Classification and Prediction
  • Decision Tree Induction
  • Bayesian Classification
  • Text Data Mining
  • Web Mining
  • Bonus Class : Regular Expression
  • Bonus Class : File Operations
  • Introduction to Computer
  • Vision and OpenCV
  • Downloading and Installing OpenCV
  • Basic Operations on Images
  • Basic Operations on Images
  • Rotating the Images
  • Drawing Functions
  • Edge Detection
  • Guassian Blur
  • Image Filtering and Threshold
  • Mouse Event
  • Template Matching
  • Video Capture
  • Face Recognition and Detection
  • Emotion Detection Project
  • Project Submission

Major Project

  • Emotion Detection
  • Face Recognition

Learning Outcomes

  • Enhance your skills by learning Data Mining and its techniques
  • Also, implement the various projects on the basis of detections and Data Science Tool-Scikit

Skill Benefit

  • Enhance Skills in Data Filtrations
  • Improved Skills in Supervised and Unsupervised Learning


Level 1

30 Hours

R Programming + Keras
  • 1:1 Personalised and Customised Live Sessions
  • Access to E-Learning Resources and Community
  • After-Class Assignments and Quizzes
  • Work on Real-Time Projects
  • Course Level Completion Certificate
  • 24x7 Customer Support


Level 2

38 Hours

SciKit and Tableau + Data Mining
  • 1:1 Personalised and Customised Live Sessions
  • Access to E-Learning Resources and Community
  • After-Class Assignments and Quizzes
  • Work on Real-Time Projects
  • Motivational Sessions
  • Course Level Completion Certificate
  • 24x7 Customer Support


Level 3

40 Hours

Data Science - Advance + AI with Python
  • 1:1 Personalised and Customised Live Sessions
  • Access to E-Learning Resources and Community
  • After-Class Assignments and Quizzes
  • Work on Real-Time Projects
  • Personality Development Sessions
  • Mindfullness Activity
  • App Deployment
  • 24x7 Customer Support
  • Course Completion Certificate

Advance Concepts of Data Science

108 Hours

R Programming and Keras + SciKit and Tableau & Data Mining + Data Science - Advance and AI with Python
  • Personalised Learning
  • Deploy your own project and App
  • Focus on Personality Development
  • Focus on Extra Curriculum Activities
  • Access of E-learning portal, Project Gallery and Community
  • Course Completion Certificate
  • Prepare for Course Certifications


AI & Data Science Projects Using Python

Advanced Data Science tools make you an expert in Machine Learning and Artificial Intelligence.

Build projects in Machine learning, Neural Networks and Artificial Intelligence using the Python Programming Language.

AI with Python

This section covers how students will develop AI projects using the Python Programming Language.

  • Introduction to Data Visualization and Tableau
  • Tableau Data Type and Sources
  • Tableau Worksheets
  • Tableau Calculations
  • Tableau Sorting and Filtering
  • Tableau Charts
  • Road Lane Line Detection
  • Credit Card Fraud Project Using R
  • Fake News Prediction Project
  • Car Price Prediction Project
  • Heart Disease Classification

Major Project

  • Car Price Prediction
  • Heart Disease Classification

Learning Outcomes

Build numerous AI Projects using Data Science Tools and Techniques with the help of Python Programming.

Skill Benefit

  • Map AI with Real World
  • Develop AI projects