Data Science and Machine Learning (Theory and Projects) A to Z

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A carefully crafted beginner’s friendly course that will equip you with all the required skills and key concepts. Learn key data science and machine learning concepts right from the beginning with examples in Python. You will also explore core concepts and methodologies of RL and Deep RL, along with several practical implementations.

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717 on-demand videos & exercises
Level: Beginner
107hrs 47mins
Access on mobile, web and TV

What to know about this course

This course is crafted to teach you the most in-demand skills in the real world. This course aims to help you understand all the data science and machine learning concepts and methodologies with regard to Python. When you take a quick look at the different sections of this course, you may think of these sections as being independent.

However, these sections are interlinked and almost sequential. Each section is an independent concept and is like a course on its own. We have deliberately arranged these sections in a sequence as each subsequent section builds upon the sections you have completed. This framework enables you to explore more independent concepts easily.

At the end of every subsection, you are assigned homework to further strengthen your learning. All these assessments are based on the previous concepts and methods you have learned. Several of these assessment tasks will be coding-based, as the main aim is to get you up and proceeding to implementations.

By the end of this course, you will be able to easily tackle real-world problems and ensure steady career growth and will be equipped with the knowledge of all the essential concepts you need in order to excel as a data science professional. The complete code bundle for this course is available at:

Who's this course for?

People who want to learn data science and machine learning with real datasets in data science, people who want to enter the field of data science from a non-engineering background, people who want to enter the field of machine learning, and people who want to learn data science and machine learning along with its implementation in practical projects are the target audience for this course.
There is no prerequisite for this course. You will begin with the fundamental ideas and gradually increase your understanding of the topic.

What you'll learn

  • Understand and visualize data with Python Explore probability and statistics in Python
  • Learn feature engineering and dimensionality reduction with Python
  • Cover artificial neural networks with Python
  • Cover CNN and RNN with Python
  • Learn deep reinforcement learning applications.

Key Features

  • Advanced and recently discovered models and breakthroughs by the champions in the AI field
  • Key data science and machine learning concepts with examples in Python
  • Detailed explanation and live coding with Python.

Course Curriculum

About the Author

AI Sciences

AI Sciences are experts, PhDs, and artificial intelligence practitioners, including computer science, machine learning, and Statistics. Some work in big companies such as Amazon, Google, Facebook, Microsoft, KPMG, BCG, and IBM. AI sciences produce a series of courses dedicated to beginners and newcomers on techniques and methods of machine learning, statistics, artificial intelligence, and data science. They aim to help those who wish to understand techniques more easily and start with less theory and less extended reading. Today, they publish more comprehensive courses on specific topics for wider audiences. Their courses have successfully helped more than 100,000 students master AI and data science.

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