Data Science Web tutorials and Mock Test with MCQs
Here are more than 10,000 MCQ Questions and Answers to assist you improve your knowledge.
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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
