Machine Learning Fundamentals Course Overview

Overview:

The Machine Learning Fundamentals course at Artisan Alley Learning provides participants with a comprehensive introduction to the principles and techniques of machine learning. This course covers essential concepts, algorithms, and applications of machine learning, empowering participants to leverage machine learning models for data-driven decision-making.

Description:

This course offers a deep dive into the foundational concepts and methodologies of machine learning. Participants will learn about supervised and unsupervised learning techniques, model evaluation, feature engineering, and more. Through hands-on exercises and real-world examples, participants will develop the skills needed to build, train, and deploy machine learning models for various applications.

Objectives:

• Understand the fundamental principles and concepts of machine learning

• Learn about different types of machine learning algorithms and their applications

• Gain practical experience in model development, training, and evaluation

• Explore best practices for feature engineering, model selection, and hyperparameter tuning

• Apply machine learning techniques to real-world data sets and problems

Course Content Overview:

Module 1: Introduction to Machine Learning

• • Overview of machine learning concepts and applications

  • Types of machine learning algorithms

Module 2: Supervised Learning

• • Regression and classification algorithms

  • Model evaluation and performance metrics

Module 3: Unsupervised Learning

• • Clustering and dimensionality reduction techniques

  • Anomaly detection and association rule learning

Module 4: Model Selection and Evaluation

• • Cross-validation and hyperparameter tuning

  • Bias-variance tradeoff and overfitting

Module 5: Feature Engineering and Preprocessing

• • Techniques for feature selection and extraction

  • Data preprocessing and normalization

Module 6: Applications of Machine Learning

• • Real-world case studies and applications of machine learning

  • Best practices for deploying and maintaining machine learning models

Potential Career Paths:

Completion of this course can lead to various career opportunities, including:

• Data Scientist

• Machine Learning Engineer

• AI Specialist

• Research Scientist

• Business Analyst

Enrollment Requirement:

Participants must possess basic computer skills and familiarity with algebra and statistics.

Benefits:

• Access to 15 downloadable ebooks covering supplementary materials and resources

• Certificate of completion upon finishing the course

• Enhanced understanding and practical experience in machine learning fundamentals