What is the syllabus for Data Science?

Algorithms, analytics, and AI models must be created and applied to analyze. It’s powered by software that sifts through data for patterns then transforms those patterns into projections to aid organizations in making better decisions. These applications are powered by a variety of algorithms and models that can predict outcomes, allowing users to make more informed decisions.

The three major components of the Data Science course syllabus are Big Data, Machine Learning, and Data Science Modeling. In this highly sought-after specialty, the contents in these three primary components span a wide range of themes.

Main Subjects are:

  • 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