Machine Learning Python Course Free

Python for Machine Learning

star 4.51  Beginner level 2.25 learning hrs 475K+ Learners

Learn Python for machine learning with NumPy arrays, array math, Pandas Series, DataFrames, Objects, and key functions. Join this free Python machine learning course to build data handling skills for real-world projects.

Instructor:

Mr. Bharani Akella

Key Highlights

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About this course

The free machine learning Python course helps you build the core Python skills needed to work with data for machine learning tasks. You will learn how to use NumPy for array creation, joining arrays, finding intersections and differences, performing array-based math, and saving or loading array data. These skills help you prepare, organize, and process numerical data more efficiently before moving into machine learning workflows. 

You will be able to use Pandas for data manipulation and analysis, including Series, DataFrames, and common functions such as mean, median, maximum, and minimum. By the end of the course, you will be able to handle data using NumPy and Pandas, perform basic data operations, and build a stronger foundation for machine learning, data analysis, and Python-based analytics projects.



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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.

Get access to the complete curriculum once you enroll in the course

This course is ideal for

  • Beginners wanting to learn Python for machine learning.
  • Students and job seekers exploring data science roles.
  • Working professionals who analyze data in Python.
  • Job seekers who want a completion certificate.

Python for Machine Learning

rating icon 4.51

2.25 Hours

Beginner

475K+ learners enrolled so far

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Learner reviews of the Free Courses

4.51
68%
24%
5%
1%
2%
Reviewer Profile

4.0

India
“Smooth Sailing Through the Easy Flow of the Course”
The course was incredibly well-structured and easy to follow. The content was presented in a logical sequence, which made grasping each concept straightforward and intuitive. The explanations were clear and concise, and the pace was just right—neither too fast nor too slow. Each module built seamlessly on the previous one, reinforcing learning and making complex topics more accessible. Overall, the smooth flow of the course significantly enhanced my understanding and kept me engaged throughout.
Reviewer Profile

5.0

India
“Excellent Python Data Science Fundamentals Course”
The course covers NumPy and Pandas concepts very effectively. The quiz questions are well-structured and test practical knowledge. Topics like ndarray, DataFrame operations, iloc/loc indexing, and array manipulation are explained clearly. Highly recommended for beginners looking to build a strong foundation in Python data science.
Reviewer Profile

5.0

India
“Engaging Content, Well-Structured, and Highly Informative!”
This course is incredibly well-structured, providing clear and concise explanations that are easy to follow. The content is both engaging and informative, making complex topics understandable. The instructor's expertise is evident, and the practical examples help solidify the concepts. Overall, it's a valuable learning experience that I highly recommend.
Reviewer Profile

4.0

India
“Comprehensive Machine Learning Course Utilizing Python”
Here's a short example of experience in Python for a machine learning course: Utilized Python to develop and deploy machine learning models, leveraging libraries like NumPy, Pandas, and scikit-learn to preprocess and visualize data, implement supervised and unsupervised learning algorithms, and evaluate model performance using metrics and cross-validation.
Reviewer Profile

5.0

India
“Transformative Learning: My Satisfying Experience with an Engaging Online Class”
Online learning in machine learning offers a flexible and accessible way to master complex concepts and techniques. With numerous platforms providing courses, tutorials, and hands-on projects, learners can engage at their own pace. This mode of education fosters collaboration through forums and discussion groups, enhancing understanding. However, the lack of in-person interaction can sometimes challenge motivation. Overall, online learning is an invaluable resource for anyone looking to deepen their knowledge in the rapidly evolving field of machine learning.
Reviewer Profile

5.0

India
“Comprehensive Foundation in Python Programming”
The engaging content, hands-on exercises, and supportive instructors make it an excellent choice for beginners and those looking to enhance their skills. Whether you’re diving into data science, web development, or automation, this course equips you with the tools to succeed.
Reviewer Profile

5.0

India
“Hands-On Approach and Interactive Sessions”
I really appreciated how the course focused on practical applications and real-world scenarios. The clarity of explanations and step-by-step guidance made complex topics much easier to grasp. Additionally, the opportunity to collaborate with peers and discuss ideas helped deepen my understanding and made the learning experience enjoyable.
Reviewer Profile

5.0

India
“Good to Learn This Course for Detailed ML in Python”
Machine learning (ML) in Python leverages libraries like scikit-learn, TensorFlow, and PyTorch to build models for tasks such as classification, regression, and clustering. Python's rich ecosystem simplifies data manipulation, model training, and evaluation, making it a popular choice for developing and deploying ML solutions.
“Great Start to Machine Learning Using Python”
This course provides you with the essential tools to kickstart your Machine Learning journey using Python in a dynamic and practical way. Perfect for those looking for an interactive approach from day one.
Reviewer Profile

5.0

India
“Introduction to Machine Learning: A Practical Approach”
This course is very helpful in gaining a foundational understanding of machine learning. The content is easy to follow, and the practical examples are great for applying the concepts. I would love to see more courses like this to help students explore new topics and improve their skills.

Our course instructor

instructor img

Mr. Bharani Akella

Data Scientist

Machine Learning Expert

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5M+ 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 will I learn in this free machine learning Python course?

The Python for Machine Learning free course teaches NumPy and Pandas for machine learning tasks. You learn NumPy arrays, array joining and intersection, differences, array math, saving and loading arrays, Pandas Series, DataFrames, and functions such as mean, median, maximum, and minimum.

Who should take this free Python machine learning course?

The free course is useful for beginners who want to build data-handling skills before moving into machine learning projects. It is listed as a beginner-level course and focuses on practical Python libraries used in ML workflows.

How long does this free Python-based machine learning course take to complete?

The free ML with Python course includes 2.25 hours of learning. It gives you a short, focused way to build Python data handling skills used in machine learning.

What skills will I gain from this free machine learning Python training course?

This free ML with Python course helps you build the following skills:

  • NumPy Arrays

  • NumPy Operations

  • NumPy Math

  • Saving & Loading NumPy

  • Pandas Series

  • Pandas DataFrame

  • Pandas Functions (Mean, Median, Max, Min)

  • Data Manipulation

  • Supervised Learning

  • Unsupervised Learning

  • Machine Learning with Python


What topics are covered if I want to learn Python for machine learning free?

This course covers the following modules:

  • Intro to Numpy

  • Joining NumPy Arrays

  • Numpy Intersection & Difference

  • Numpy Array Mathematics

  • Saving and Loading Numpy Array

  • Intro to Pandas

  • Pandas Series Object

  • Intro to Pandas Dataframe

  • Pandas Functions


Does this Python machine learning fundamentals course free include practical examples?

The machine learning Python course includes worked examples and code for NumPy and Pandas. You learn by seeing how arrays, dataframes, and functions work in practical Python tasks.

How does this free Python machine learning course help with real ML projects?

The Learn Python for Machine Learning free course helps you clean, organize, transform, and analyze data using NumPy and Pandas. These are core steps before building machine learning models, because ML projects depend on well-prepared data.



Will this free online Python course on machine learning teach both NumPy and Pandas?

The Python for Machine Learning free course covers both libraries. NumPy is used for arrays, mathematical operations, and data I/O, while Pandas is used for Series, DataFrames, and common data analysis functions.



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. 

 

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

Once you enroll in the Free 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. 

 

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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