Data Science Web tutorials and Mock Test with MCQs
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Data Science


Data Science Syllabus

  • Algorithms used in Machine Learning
  • Application Based Programming in Python
  • Applied Mathematics and Informatics
  • Applied Statistical Analysis
  • Artificial Intelligence
  • Basic Statistics
  • Big Data Fundamentals and Hadoop Integration with R
  • Business Intelligence
  • CAD Design
  • Cloud Computing
  • Communication and Presentation
  • Computer Networks
  • Computing for Data Science
  • Data Acquisition and Data Science Life Cycle
  • Data handling and Visualization
  • Data Mining
  • Data Mining, Data Structures, and Data Manipulation
  • Data Scientist Roles and Responsibilities
  • Data Structures & Algorithms
  • Data Structures and Program Design in C
  • Data Structures Using C
  • Data Visualization
  • Data Warehousing
  • Data Warehousing and Multidimensional Modelling
  • Deploying Recommender Systems on Real-World Data Sets
  • Discrete Mathematics
  • Engineering Chemistry
  • Engineering Physics
  • Experimentation, Evaluation and Project Deployment Tools
  • Information Security and Privacy
  • Information Visualisation
  • Introduction and Importance of Data Science
  • Introduction to Artificial Intelligence
  • Introduction to Artificial Intelligence and Machine Learning
  • Introduction to Data Science
  • Introduction to Data structures and Algorithms
  • Introduction to Statistical Learning
  • Machine Learning
  • Mathematical Foundations of Data Science
  • Matrix Computations for Data Science
  • Model selection and evaluation
  • Object-Oriented Programming in Java Machine Learning
  • Operating Systems
  • Operations Research and Optimization Techniques
  • Optimization for Data Science
  • Optimization Techniques
  • Predictive Analytics and Segmentation using Clustering
  • Principles of Electrical and Electronics Engineering
  • Probability and Inferential Statistics
  • Python Programming Lab
  • Scientific Computing
  • Software Engineering and Testing Methodologies
  • Statistical Foundations for Data Science
  • Statistics
  • Stochastic Models
  • Storytelling with Data
  • Understanding Exploratory Data Analysis
  • Working on Data Mining, Data Structures, and Data Manipulation



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▾ Multiple Choice Question (MCQs)