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Applied Data Science

via SWAYAM Plus

Overview

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Applied Data Science course (in collaboration with Google) immerses students in the practical application of data analysis techniques, statistical modeling, machine learning algorithms, and data visualization tools to derive insights, make predictions, and solve real-world problems using large and complex datasets. Students explore data preprocessing, feature engineering, model selection, and evaluation methods through hands-on projects and case studies. With a focus on applying data science methodologies to diverse domains such as business analytics, healthcare, finance, and social sciences, the course equips participants with the skills and knowledge to extract valuable insights from data, drive informed decision-making, and create data-driven solutions that address contemporary challenges in various industries.

Intended audience

Data Analyst, Data Scientist, Machine Learning Engineer, ML Developer, AI/ML Product Manager

Prerequisites

  • BE/BTech, ME/MTech, Bsc, Msc, BCA, MCA

Assessment & certification

  • Assessment fee: Included — no extra fee
  • Assessment mode: Online proctored
  • Assessment type: Project-Based Assessment & Quiz
  • Assessment provider: Smartbridge
  • Certificate provider: Data Analyst, Data Scientist, Machine Learning Engineer, ML Developer, AI/ML Product Manager

NCrF level: 5.5 (NCrF credit-eligible)

Syllabus

  • Week 1: Introduction to Machine Learning
  • Week 2: Introduction to Python
  • Week 3: Python Libraries for Machine Learning (Numpy, Pandas, Matplotlib, Seaborn, Scikit-learn, Tensorflow, Keras
  • Week 4: Mathematics for Data Science
  • Week 5: Statistics, EDA, Data Preprocessing & Feature Engineering
  • Week 6: Supervised Learning Algorithms (Regression & Classification)
  • Week 7: Unsupervised Learning Algorithms (Clustering)
  • Week 8: Neural Network
  • Week 9: Parameter Optimization
  • Week 10: Web Application Development using Flask

Taught by

Hari Prabu

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