Machine Learning Python Course Free

Python for Machine Learning

star 4.51  Beginner level 2.25 learning hrs 475.8K+ 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

475.8K+ learners enrolled so far

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Reviewer Profile

5.0

★★★★ ★
India
“The Python for Machine Learning Course Provides a Solid Foundation”
The Python for Machine Learning course provides a solid foundation in using Python for building machine learning models. It covers essential libraries like NumPy, pandas, and scikit-learn, and introduces important concepts such as data preprocessing, model training, and evaluation. The course is practical and hands-on, with lots of coding exercises and real-world examples. It's a great starting point for anyone looking to apply Python to machine learning tasks, with clear explanations and useful resources.
Reviewer Profile

5.0

★★★★ ★
India
“Key Takeaways from My Learning Journey”
When reflecting on my learning experience, what I liked most was the opportunity to dive deep into subjects I’m passionate about and the ability to apply that knowledge in practical settings. The interactive nature of the lessons made the concepts easier to grasp and more engaging. I appreciated the balance between theory and hands-on practice, which allowed me to see real-world applications of what I was learning. Additionally, the collaborative environment was a highlight for me. Working with peers from diverse backgrounds provided new perspectives and enriched my understanding. The support from instructors and access to resources also played a significant role in making the learning process smooth and enjoyable. Overall, the combination of a well-structured curriculum, interactive tools, and a supportive community made this learning experience highly rewarding.
Reviewer Profile

5.0

★★★★ ★
India
“Earning My Certificate Was an Enriching Journey”
In a learning course, I love the structured approach that gradually builds knowledge, the opportunity to explore diverse topics, and the interactive elements that deepen understanding. Engaging with peers and instructors enriches the experience, while practical projects and real-world applications make the learning process more relevant and rewarding.
Reviewer Profile

5.0

★★★★ ★
India
“Engaging with Diverse Concepts and Solving Complex Problems”
Great learning transforms understanding through deep engagement and exploration. It involves embracing challenges, experimenting with new ideas, and reflecting on experiences. Effective learning combines theoretical knowledge with practical application, encourages curiosity, and fosters critical thinking, leading to personal and professional growth and the development of valuable skills.
Reviewer Profile

4.0

★★★ ★ ☆
India
“It Was Great to Learn Machine Learning with Python”
Great experience, loved the video, gained more knowledge, and it was helpful.
Reviewer Profile

5.0

★★★★ ★
Indonesia
“Fun and Very Useful, I Will Recommend to My Friends”
The material supports lectures and is easy to understand. I will recommend it to my friends.
Reviewer Profile
Mansoor Ahmad

5.0

★★★★ ★
“Covered the Topics in Depth and Explained Very Well”
All the essentials of both libraries, i.e., NumPy and pandas, have been covered.
Reviewer Profile

4.0

★★★ ★ ☆
United States
“Easy to Understand and Amazing Curriculum”
It was easy to understand and an amazing curriculum. Good explanation of the content.
Reviewer Profile

5.0

★★★★ ★
India
“Great Learning as the Name of This Website”
So happy to get certified from here by getting a certificate in Python language free of cost. Otherwise, outside this course is chargeable at a high rate. Thank you.
Reviewer Profile

5.0

★★★★ ★
India
“Python with Machine Learning Fundamentals”
Very useful for a person like me, easy to get a certificate for free.

Our course instructor

instructor img

Mr. Bharani Akella

Data Scientist

Machine Learning Expert

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5.1M+ 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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