Machine Learning Fundamentals

Learn the essentials at a minimum cost!

Machine Learning is a key to develop intelligent systems and analyze data in science and engineering. It has emerged as one of the most valuable and time investing domains in the current century. This course is designed for all the learners interested in starting their journey with Machine Learning. The course explains all the important concepts in machine learning. It covers a wide range of topics including types of machine learning, applications and use cases, certifications and job roles.

What you’ll learn

  • Learn about all the basics to start with Machine Learning.
  • Understand the different types of Machine Learning algorithms.
  • Understanding various python libraries used in Machine Learning.
  • A mini project to implement the skills.
  • Learn about supervised and unsupervised machine learning.

Course Content

  • Introduction –> 6 lectures • 7min.
  • Machine Learning Algorithms –> 10 lectures • 13min.
  • Learning And Opportunities –> 4 lectures • 9min.
  • Basics Of Algorithms –> 3 lectures • 2min.
  • Classification –> 7 lectures • 8min.
  • Regression –> 3 lectures • 3min.
  • Clustering –> 2 lectures • 3min.
  • Association –> 2 lectures • 1min.
  • Python Libraries –> 2 lectures • 1min.
  • Numpy –> 4 lectures • 4min.
  • Pandas –> 3 lectures • 2min.
  • Matplotlib –> 2 lectures • 2min.
  • Seaborn –> 3 lectures • 4min.
  • Scikit Learn –> 1 lecture • 1min.
  • Types Of Algorithms –> 3 lectures • 1min.
  • Algorithms In Regression –> 7 lectures • 2min.
  • Algorithms In Classification –> 14 lectures • 8min.
  • Algorithms In Clustering –> 3 lectures • 1min.
  • Algorithms In Association –> 3 lectures • 1min.
  • Fundamentals Completition –> 1 lecture • 1min.
  • Final Milestone! –> 2 lectures • 10min.

Machine Learning Fundamentals

Requirements

  • No programming experience needed. All the concepts are taught from basics..

Machine Learning is a key to develop intelligent systems and analyze data in science and engineering. It has emerged as one of the most valuable and time investing domains in the current century. This course is designed for all the learners interested in starting their journey with Machine Learning. The course explains all the important concepts in machine learning. It covers a wide range of topics including types of machine learning, applications and use cases, certifications and job roles.

The course also explains different algorithms in machine learning and a simple mini project with a real life application and implementation. The course will help the learners to clear all the fundamentals and enhance their existing skillset. Machine Learning concepts are implemented using python and basics of all the libraries is also been taught in the course itself. The course is a combination of conceptual theory as well as practical examples and real life project to help the students get ready for your journey.

 

The key takeaways from the course are :

  • Knowledge about supervised machine learning
  • Knowledge about unsupervised machine learning
  • Study of algorithms
  • Applications of machine learning algorithms
  • Advantages and disadvantages
  • Information about the various certifications in the domain
  • Information about job roles in the domain
  • Implementation of algorithms in real life project
Get Tutorial