Machine Learning & AI Basics Course Roadmap

Why Learn From Wakeupcoders?

  • 9+ Years Experienced AI & ML Experts
  • Trained 12,000+ Students Worldwide
  • Latest Curriculum Covering AI & ML Trends
  • 100% Skill Learning Guarantee
  • AI-Based Learning Infrastructure to Optimize Learning & Development

Machine Learning & AI Basics Course Modules

Module 1: Introduction to AI & Machine Learning

Understanding the fundamentals of AI and ML. Topics covered:

  • What is Artificial Intelligence?
  • History and Evolution of AI & ML
  • Types of Machine Learning (Supervised, Unsupervised, Reinforcement Learning)
  • Real-World Applications of AI

Module 2: Mathematics for Machine Learning

Strengthening the mathematical foundation. Topics covered:

  • Linear Algebra Basics
  • Probability and Statistics
  • Calculus for Optimization
  • Matrix Operations and Vector Spaces

Module 3: Programming for AI & ML

Hands-on coding and implementation. Topics covered:

  • Introduction to Python for AI
  • Essential Python Libraries: NumPy, Pandas, Matplotlib
  • Data Structures and Algorithms for ML
  • Jupyter Notebook and Google Colab Basics

Module 4: Data Preprocessing & Feature Engineering

Preparing data for machine learning models. Topics covered:

  • Data Cleaning and Handling Missing Values
  • Feature Scaling and Normalization
  • Data Transformation Techniques
  • Dimensionality Reduction Methods

Module 5: Supervised Learning Algorithms

Understanding predictive modeling techniques. Topics covered:

  • Regression Algorithms (Linear Regression, Logistic Regression)
  • Classification Algorithms (Decision Trees, Random Forest, SVM)
  • Model Evaluation Metrics (Accuracy, Precision, Recall, F1-Score)

Module 6: Unsupervised Learning Algorithms

Learning from unstructured data. Topics covered:

  • Clustering Algorithms (K-Means, Hierarchical Clustering)
  • Association Rule Learning (Apriori, FP-Growth)
  • Principal Component Analysis (PCA)

Module 7: Neural Networks & Deep Learning Basics

Introduction to modern AI techniques. Topics covered:

  • Basics of Neural Networks
  • Activation Functions and Loss Functions
  • Introduction to TensorFlow and Keras
  • Implementing a Simple Neural Network

Module 8: Model Deployment & AI Ethics

Bringing AI models into real-world applications. Topics covered:

  • Model Deployment Techniques (Flask, FastAPI)
  • AI Bias and Fairness
  • Ethical Considerations in AI Development
  • Future Trends in AI & ML

Mini Projects

Minimum 3+ mini-projects to apply your learning:

  • Predicting House Prices using Regression
  • Customer Segmentation using Clustering
  • Sentiment Analysis using NLP

Lab Sessions

10 hands-on coding practice sessions:

  • Implementing Regression & Classification Models
  • Data Visualization and Feature Engineering
  • Training Neural Networks with TensorFlow

Certification

Complete assignments, projects, and tests to earn a Wakeupcoders AI & ML Basics Certification, adding value to your resume.

Course Fee Structure

  • Full Payment: Rs. 40,000/-
  • EMI Options: No-cost EMI plans in 3–4 installments

Class Schedules at Wakeupcoders

  • Online Instructor-Led Course
  • Online Self-Paced Course
  • Free One-Year Access to Course Materials

Placement Assistance

  • Resume Building Guidance
  • Interview Preparation
  • Freelancing and Job Market Strategies

Mock Interviews

  • Conducted with Industry Experts
  • Personalized Feedback for Improvement

Contact Us

For more details and enrollment, reach out to us at: wakeupcoders.com/contact

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Wakeupcoders - Digital Marketing & Web App Company
Wakeupcoders - Digital Marketing & Web App Company

Written by Wakeupcoders - Digital Marketing & Web App Company

We make your business smarter and broader through the power of the internet. Researcher | Web developer | Internet of things | AI | www.wakeupcoders.com

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