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Data Science

A study states that over 2.5 quintillion bytes of data are being generated every single day which is unstructured or semi-structured.

To process the massive amounts of data we need more effective algorithms. This is made possible by the Application of Data Analytics. Data Analytics is the application of structured statistical and mathematical techniques on collected data in order to detect underlying patterns as well as make predictions.

Benefits of Data Analytics

Data Science Syllabus

Want to know about the syllabus of Data Science? The Data Science course syllabus comprises three main components, i.e. Big Data, Machine Learning and Modelling in Data Science. Across these three main components, the subjects are cover varied areas of this sought-after discipline. Here is the complete Data Science Syllabus:

  • Introduction to Data Science
  • Mathematical & Statistical Skills
  • Machine Learning
  • Coding
  • Algorithms used in Machine Learning
  • Statistical Foundations for Data Science
  • Data Structures & Algorithms
  • Scientific Computing
  • Optimization Techniques
  • Data Visualization
  • Matrix Computations
  • Scholastic Models
  • Experimentation, Evaluation and Project Deployment Tools
  • Predictive Analytics and Segmentation using Clustering 
  • Applied Mathematics and Informatics
  • Exploratory Data Analysis
  • Business Acumen & Artificial Intelligence

Data Science Syllabus for Beginners

If you are a beginner in data science, there are various introductory courses available online which you can take to familiarise yourself with the basics. Here is an overview of the Data Science syllabus for Beginners:

  • Introduction to Data Science
  • Understanding Exploratory Data Analysis
  • Machine Learning
  • Model selection and evaluation
  • Data Warehousing
  • Data Mining
  • Data Visualization
  • Cloud Computing
  • Business Intelligence
  • Storytelling with Data
  • Communication and Presentation
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