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Machine Learning Basics: Introduction to Machine Learning

via SWAYAM Plus

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Overview

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This beginner-friendly course introduces learners to the fundamental concepts of machine learning, its real-world applications, and model-building techniques. Covering supervised and unsupervised learning, data preprocessing, model evaluation, and practical tools like Scikit-learn and Azure ML Studio, the course lays a strong foundation in predictive analytics and intelligent systems.

Intended audience

Intended audience

Prerequisites

  • Basic understanding of mathematics and statistics - Familiarity with Python programming recommended - Ideal for students, professionals, and enthusiasts curious about AI/ML

Assessment & certification

  • Assessment fee: Included — no extra fee
  • Assessment mode: Online proctored
  • Assessment type: Project-Based
  • Assessment provider: Hoping Minds
  • Certificate provider: SWAYAM Plus and Hoping Minds

NCrF level: 6 (NCrF credit-eligible)

Syllabus

  • Week 1: Introduction to Machine Learning and its types
  • Week 2: Data collection, cleaning, and preprocessing
  • Week 3: Supervised Learning: Regression and Classification
  • Week 4: Unsupervised Learning: Clustering and Dimensionality Reduction
  • Week 5: Feature engineering and model optimization
  • Week 6: Evaluation metrics: Accuracy, Precision, Recall, F1-score
  • Week 7: ML implementation with Scikit-learn and Azure ML Studio
  • Week 8: Capstone project on real-world ML problem

Taught by

Ms. Aastha Sharma

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