Introduction to Machine Learning for Begineers[Data-science]

Introduction to Machine Learning for Begineers[Data-science] udemy course

Learn about Data Science and Machine Learning with Python including Pandas, matplotlib with projects,quizes

HERE IS WHY YOU SHOULD TAKE THIS COURSE

This course completely guides you through both supervised and unsupervised learning using Python. This means this course covers all the main aspects of practical data science, and if you take this course, you can be done with taking other courses or buying books on Python-based data science.

In this age of big data, companies across the globe use Python to sift through the avalanche of information at their disposal.

By becoming proficient in supervised and unsupervised learning in Python, you can give your company a competitive edge and boost your career to the next level.

LEARN FROM AN EXPERT DATA SCIENTIST WITH 3+ YEARS OF EXPERIENCE

My name is Aakash Singh and I have also recently published my research paper in the International Journal IJSR on Machine Learning Datasets.

This course will help you gain a robust grounding in the main machine learning clustering and classification techniques.

NO PRIOR PYTHON OR STATISTICS OR MACHINE LEARNING KNOWLEDGE IS REQUIRED

You will start by absorbing the most valuable Python data science basics and techniques.

I use easy-to-understand hands-on methods to simplify and address even the most difficult concepts in Python.

My course will help you implement the methods using real data obtained from different sources. After taking this course, you will easily use packages like NumPy, Pandas, and Matplotlib to work with real data in Python.

We will go through lab sessions on Jupyter Notebook terminal. We will explore lots of real-life examples to increase practical knowledge of programming. We will also cover theoretical sections, which are essential for this course. By the end of this course, you will be able to code in Python and feel confident with machine learning, enabling you to create your own programs and implement them where needed.

Most importantly, you will learn to implement these techniques practically using Python. You will have access to all the data and scripts used in this course. Remember, I am always here to support my students.

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