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Overall Score : 74 / 100

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Course Description

Master the basics of Pythons and Machine Learning from scratch. If you are looking for good start in Machine Learning this is the course for you to start with. This course is design in such a way which need only minimum or no programming experience from participants. This course will walk you towards every step of Python and Machine learning starting from the history, setup and exercises in Python and Machine learning. With every tutorial you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science. This course focuses more on practical aspect rather than theoretical aspect of programming. In this course you will cover the following topics in much greater details.:
  1. Introduction to Python
  2. Python Data Types
  3. Control Flow
  4. Function, Modules and Packages
  5. I/O errors and Exceptions
  6. Classes
  7. Standard Libraries
  8. Numpy
  9. Metplotlib
  10. Pandas
  11. Machine Learning
  12. Introduction to Machine Learning
  13. Introduction to Scikit
  14. Installing Scikit - learn
  15. Introduction and Installing Jupyter Notebook
  16. Techniques Of Machine Learning
  17. Supervised Machine Learning
  18. Unsupervised Machine Learning
  19. Types of Machine Learning Algorithms
  20. Classifications
  21. and many more.
Who is the target audience?
  • Anyone interested in Machine Learning.
  • Students who have at least high school knowledge in math and who want to start learning Machine Learning.
  • Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning.
  • Any people who are not that comfortable with coding but who are interested in Machine Learning and want to apply it easily on datasets.
  • Any students in college who want to start a career in Data Science.
  • Any data analysts who want to level up in Machine Learning.
  • Any people who are not satisfied with their job and who want to become a Data Scientist.
  • Any people who want to create added value to their business by using powerful Machine Learning tools.

Who this course is for:
  • Beginner Python developer curious about Python and Machine Learning programming

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Instructor Details

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Girish Kumar Shakya Mobile : +91 - " 8085953911 DOB : 14 - " March - " 1980
Professional Summary

  • Having 11+ years of Teaching and Industry experience in Android, J2ME, Blackberry JDE, PhoneGap, Sencha, Java, Struts , JEE6, EJB and Kotlin.
  • Google Android Trainer for Android Skilling Programs in various universities in India.
  • Experience in Android Architect Development.
  • Experience in Java Database Connectivity (JDBC)
  • Experience in Oracle.
  • Experience in Java DB
  • Experience in SQLite.
  • Experience in working with Restful webservice XML/JSON
  • Well versed in Model View Controller.
  • Well versed in Model View Presenter.
  • Well versed in Operating System Windows/Max/Linux.
  • Well versed in Android Studio.
  • Well versed in Eclipse IDE.
  • Self Motived and highly adaptable in terms of new requirements , meeting Deadlines, Delivering Quality Inputs.
  • An enthusiastic team - " oriented team member with excellent communication skills to develop creative for challenging client needs.
  • Good Knowledge over UML.

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More courses by Girish Shakya

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Reviews

3.7

7 total reviews

5 star 4 star 3 star 2 star 1 star
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By Animesh Kumar

It's very basic and the trainer is not quite good at explaining things in a better and lucrative manner.

By Antonietta Conte

Definitely yes!

By Aayushi Kesharwani

It's an amazing course to get a basic idea about python and machine learning.

By Tanu Gupta

There is no proper description of each topic

By Tolga macit

great way to start working on machine learning 100% recommended for beginners

By Amit Mishra

yes the course is transfer knowledge able content and it good for begineer

By Ojaswini Nimbalkar

there's always scope for improvement.