Free Course on Machine Learning Using Python

Python for Machine Learning

star 4.51  Beginner level 2.25 learning hrs 465K+ Learners

Secure a score in the leading technology domains by taking this Python for Machine Learning course. Master NumPy and Pandas tools and techniques for arrays, intersection, objects, and functions for free online.

Instructor:

Mr. Bharani Akella

Key Highlights

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About this course

The Python Programming for Machine Learning course shall focus you on the elements and features available in Python programming for Machine Learning tasks, along with a few demonstrated samples. It shall begin with introducing you to the NumPy library and continue with helping you understand its arrays, intersection, differences, loading, and saving as you follow the first half of the course.

 

The second part engages you by covering Pandas library and its objects, dataframes, and functions. Take up the quiz at the end of the course to test your skills and evaluate your gains to secure your certificate. 

 

Enroll in the Machine Learning course and embark on your career with the professional Post Graduate certificate. After this free, self-paced, beginner's guide to Python for Machine Learning, you can escalate your learning to different concepts in Machine Learning in depth with millions of aspirants across the globe!

 

Great Learning offers a free course on Python for machine learning. This course provides comprehensive coverage of the fundamentals of Python programming for data science, machine learning and AI. It includes topics such as Python data structures, functions, classes, file handling, web scraping, data visualization, machine learning algorithms, deep learning, and more. 


The course covers the fundamentals of Python and its use in the context of data science and machine learning. It also covers the basics of supervised and unsupervised learning, and helps students gain a strong understanding of the principles of data science and machine learning. The course provides hands-on experience and code examples to help learners understand complex concepts and apply them in a practical setting. With this course, learners can gain a deep understanding of the Python programming language and its potential applications in data science and machine learning. 

Course outline

Intro to Numpy

In this section, you will be introduced to the NumPy library to add functions and methods to the program without actually writing the code.

Joining NumPy Arrays

There are three different modules to join Numpy arrays: vstack, hstack, and column stack. You will learn all these methods one by one in this module. 
 

Numpy Intersection & Difference

We shall understand what sect difference and intersection are at the beginning of this section. We shall then understand how to extract the exact elements by excluding other elements from the array with demonstrated code snippets.

Numpy Array Mathematics

This section will explain and demonstrate working with various mathematical operations using arrays like sum, increment, mean and median.

Saving and Loading Numpy Array

We will understand how to load and store a NumPy array in this section. We shall learn to work with arrays, starting from creating a NumPy array to storing and loading it with demonstrated sample codes.

Intro to Pandas

We shall understand Panel Data for data manipulation and analysis in Python. 

 

Pandas Series Object

We shall understand one-dimensional labeled arrays in this section. We will learn to import the Pandas library, create a series object using the inbuilt data type, and work with it with demonstrated code snippets.

Intro to Pandas Dataframe

After understanding the basics of Pandas Dataframe, you will learn to work with it through a sample demonstration in this section. 

 

Pandas Functions

We shall discuss the Pandas functions like mean, median, maximum, and minimum in this section. We shall also understand working with different methods for each of these functions.

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Python for Machine Learning

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2.25 Hours

Beginner

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465K+ learners enrolled so far

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Learner reviews of the Free Courses

4.51
68%
24%
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Reviewer Profile

5.0

My Experience About This Course Was Great
I really enjoyed the course, and the course flow is very easy to understand. I love having this course. The learning experience is really great.
Reviewer Profile

4.0

The Hands-On Projects and Real-World Datasets Provided Excellent Practical Experience
This course was a great introduction to Python for Machine Learning. I really enjoyed the clear explanations of core concepts like supervised learning, unsupervised learning, and deep learning. The hands-on labs with libraries like TensorFlow, Keras, and Scikit-learn helped solidify my understanding. I also appreciated the focus on real-world applications and the opportunities to work on projects that applied these techniques to real datasets. Overall, it's a great course for anyone looking to build a strong foundation in machine learning with Python.
Reviewer Profile

5.0

Great Learning: Bridging Knowledge and Industry Skills
Great Learning offers exceptional courses on NumPy, Pandas, and introductory AI and machine learning. The classes are well-structured, providing a solid foundation in data manipulation and analysis. Instructors are highly knowledgeable and offer real-world insights, making complex topics easy to understand. The hands-on projects reinforce learning and prepare students for industry challenges. This platform is perfect for anyone looking to enhance their skills and advance in the field of data science and AI. Highly recommended!
Reviewer Profile

5.0

Quality and Usability of the Course
It was an easy-to-use and applicable course. My data analysis journey started with your courses.
Reviewer Profile

4.0

Python for Machine Learning (NumPy and Pandas)
The "Python for Machine Learning" course at Great Learning offers a thorough introduction to key machine learning concepts and practical applications. The course content is well-structured, covering essential topics such as data preprocessing, feature engineering, and model evaluation. The hands-on projects and coding exercises provide valuable practical experience, reinforcing theoretical knowledge. The instructor's clear explanations and real-world examples greatly enhance the learning experience.
Reviewer Profile

4.0

Really Enjoyed the Lesson. It Was Easy to Follow and Well-Structured
I really enjoyed the lesson. It was easy to follow and well-structured, making the concepts clear and understandable. The explanations were concise, and the examples helped reinforce the material. Overall, it was an engaging and informative session that kept me interested throughout.
Reviewer Profile

5.0

Highlight of Your Learning Experience: I Enjoyed the Hands-On Projects and Collaborative Discussions
I thoroughly enjoyed the hands-on projects that allowed me to apply theoretical concepts in practical scenarios. Collaborative discussions with peers enhanced my understanding and provided diverse perspectives, making the learning process more engaging and enjoyable.
Reviewer Profile

5.0

Comprehensive Introduction to Pandas and NumPy in Machine Learning
I recently completed the Python for Machine Learning course with Great Learning, and I found it very informative and practical. The introduction to pandas and NumPy was particularly helpful, and the exercises gave me a solid hands-on experience with these libraries. The instructors were clear and made the concepts easy to understand. However, I would have appreciated more complex real-world examples in the exercises. Overall, it was a great learning experience!
Reviewer Profile

5.0

Amazing Experience, Very Informative
I enjoyed the fact that it was easy to follow and quite informative.
Reviewer Profile

5.0

An Exceptional Learning Experience with Great Learning
Great Learning provides excellent courses with engaging content and support.

What our learners enjoyed the most

Our course instructor

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Mr. Bharani Akella

Data Scientist

Machine Learning Expert

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4.9M+ Learners
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125 Courses
Bharani has been working in the field of data science for the last 2 years. He has expertise in languages such as Python, R and Java. He also has expertise in the field of deep learning and has worked with deep learning frameworks such as Keras and TensorFlow. He has been in the technical content side from last 2 years and has taught numerous classes with respect to data science.

Frequently Asked Questions

Will I receive a certificate upon completing this free course?

Yes, upon successful completion of the course and payment of the certificate fee, you will receive a completion certificate that you can add to your resume.

Is this course free?

Yes, you may enroll in the course and access the course content for free. However, if you wish to obtain a certificate upon completion, a non-refundable fee is applicable.

What are the prerequisites required to learn the Python for Machine Learning course?

Python for Machine Learning is a beginner's course, and you can begin the course with good knowledge of Python programming. However, if you are not familiar with it, we have a free Python fundamentals course that will clear your prerequisites.

Will I have lifetime access to this free course

Yes, once you enroll in the course, you will have lifetime access to this Great Learning Academy's free course. You can log in to the course and learn whenever you want to. 

 

What are my next learning options after this Python Programming for Machine Learning course

Once you complete this free course, you can opt for a Post Graduate Program in Artificial Intelligence and Machine Learning that will help advance your career growth in this leading field.

 

 

Is it worth learning Python Programming for Machine Learning?

Yes, it is beneficial to learn Python for Machine Learning. Machine Learning being one of the leading technologies in the world today, the market for machine learning professionals only grows every day. If you are thorough with Python programming, it serves as a one-stop to efficiently carry out many functions and operations using Python libraries such as Pandas, NumPy, and Matplotlib tasks in Machine Learning efficiently. 

 

What is Python programming in Machine Learning used for?

Python programming language has libraries and packages that make it straightforward and easier for the programmers to work on certain functions, operations, and tasks in Machine Learning. Also, elements like arrays, objects, intersects, dataframes, loading, and storing make the task more efficient in handling data.  

 

 

Why is Python for Machine Learning so popular?

Python is a user-friendly programming language that can be used to work with many tasks using in-built libraries such as Pandas, NumPy, and Matplotlib. The essential mathematical functions, loading, and storing operations are carried out by any machine learning professional to understand and work with data. Python provides inbuilt libraries and packages to carry out these functions more efficiently, making it a popular tool for Machine Learning purposes. 

 

 

Will I get a certificate after completing this free Python for Machine Learning course?

Yes, you will get a certificate of completion for the Python for Machine Learning course after completing all the learning modules and cracking the quiz/assessment. The assessment helps test your knowledge on the subject and badges your skills. 

 

What knowledge and skills will I gain upon completing this course?

You will gain the foundational knowledge of using Python Programming for Machine Learning tasks through this course. You will get familiar with arrays, intersect, difference, objects, series, dataframes, and functions concepts using Python programming for Machine Learning upon completion. 

 

How much does this Python for Machine Learning course cost?

This is an entirely free course from Great Learning Academy. Anyone interested in learning Python programming for Data Machine Learning and understanding its basics can get started with this course.

Is there any limit on how many times I can take this free course?

Once you enroll in the Python for Machine Learning course, you have lifetime access to it. So, you can log in to this course anytime and learn it at your pace for free online. 

 

Can I sign up for multiple courses from Great Learning Academy at the same time?

Yes, you are free to enroll in as many courses as you want from Great Learning Academy. There is no stricture on the number of courses you can enroll in at once. The courses offered by Great Learning Academy are free, so we suggest you learn one by one to get the best out of them. 

 

Why choose Great Learning Academy for this free R for Data Science course?

Great Learning is an educational technology platform dedicated to the development of talented professionals around the world. Great Learning Academy is a project of Great Learning that offers free online courses to help people advance in their careers. Over 4 million students from 140 countries have benefited from Great Learning Academy's free online courses with completion certificates. It's a one-stop-shop for all of a student's requirements.

This course is not only free and self-paced, but it also includes solved questions, proven solutions, and presented examples to help you grasp the subject's many facets. The course is taught by subject matter specialists and is specifically designed for both beginners and professionals.

 

Who is eligible to take this course?

Anybody with basic knowledge of computer science, Machine Learning, with a good hold on Python Programming, interested in learning Python concepts to work with Machine Learning tasks, and understanding its basics can take up the course. So, enroll in our course today and learn it for free online. But if you are not already familiar with the prerequisite, enroll in our free machine learning course before taking up this course. 

 

What are the steps to enroll in this Python for Machine Learning course?

Enrolling in Great Learning Academy's Machine Learning with Python is a simple and straightforward approach. You will have to sign-up with your E-Mail ID, enter your user details, and then you can start learning at your own pace. 

 

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