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Data Science & Machine Learning Projects Mastery

Data Science & Machine Learning Projects Mastery

Learn data science step-by-step with real-world analytics training in data modeling. Join millions of learners from around the world already learning on Udemy.

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What you'll learn

  • Learn Model Deployment on Amazon Web Service(AWS), Google Cloud(GCP), Microsoft Azure, Heroku, Flask API, Streamlit
  • Learn how to build machine learning model with algorithms
  • Understand the implementation of machine learning algorithms
  • Become confident in explaining data science code during interviews
  • Build your own Deep learning algorithm
  • Build your own Neural Network
  • Build your own Computer Vision Apps
  • Build your own Natural Language Processing(NLP) Apps
  • Do Virtual Internship and Hackathons


Since 2016, Data Science has remain the sexiest and the most sort after career in the world.

Data Scientist command huge salaries and many companies spend most of their budget hiring skilled Data Scientist to optimize their products.

Over the past 2-3 years, getting a Data Science job has become very competitive due to its lucrative salaries and working conditions. A lot more people now desire to be Data Scientist than any other field making the field even more competitive.

Recruiters have changed their strategies of recruiting candidates for Data Science roles.

Hiring managers have shifted their focus from just certificate qualification of applicants to considering their portfolio and projects.

The only way to get ahead of the competition is to build a stunning portfolio that will catch the attention of recruiters of your skillset. There is no better way to make recruiters know that you are the right candidate than showing your project portfolio.

In this course, you will learn along the carefully selected projects and practice to really understand how the various Machine Learning algorithms are implemented. Also practicing alongside will aid you to be in control and explain the concepts during your interview sessions.

Instructor -  Dr. Bright (PhD Data Science)

4 Courses

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