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Machine Learning Basic to Advanced - Self Paced

Self-Paced Course
interested count58k+ interested Geeks

This beginner to advanced level Machine Learning- Self Paced Course will help you learn all about ML, Data Processing, NLP & all other important topics. Also includes Machine Learning projects for a hands on learning experience.

levelBeginner to Advancecourse duration4 Weeks
interested count58k+ interested Geeks
Lifetime AccessComprehensive LearningIndustry ReadinessCapstone Projects

Course Overview

Machine Learning is one of the most exciting technologies that one would ever come across. As is evident from the name, it is the technology that gives a program: The ability to learn. But even the machines cannot start learning on their own. Right? This is where YOU come in! Learn more about what machine learning is.

This Machine Learning Self-Paced Course will help you get started with the basics of ML, before moving on to advanced concepts. You will start off by getting introduced to topics such as: What is ML, Data in ML, and other basic concepts required to help build a strong base. You will get also get introduced to other important ML and AI concepts such as Regression, Classification, Clustering and will get to learn all about NLP. This self-paced course now also includes a host of real life Projects, which will give you real-time exposure on the topics of Sentiment Analysis, GDP Analysis, Text Encoding Decoding, Text Summarisation, among many others.

Mentored by industry experts who have years of experience in ML and many industry-based projects, you will surely go on to create a name for yourself in the field of Data Science and Artificial Intelligence. So wait no more, enter the world of AI and ML today!

Pre-requisite: Basics of Python Programming Language.

Once you are done with this self paced ML Course, it is recommended for you to check out Data Science-Live Classes and advance your career as a data scientist!

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What you will learn

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What you will learn

  • How to handle data efficiently 

  • Python tools related to Data Science

  • Complete Mathematical understanding of Machine Learning

  • Application of Machine Learning Models to solve real-life problems

Course Content

01Machine Learning Understanding

Get answers to all Machine Learning related questions, What is ML, Data in ML, Anaconda, Jupyter Notebook etc

02Handling Data

Learn about Numpy, Pandas, Matplotlib, Array Dimension, Categorical Data, Data Splitting, Data Scaling, Handling Missing Data etc 

03Regression

Learn about Linear Regression, Polynomial Linear Regression, Support Vector, Decision Tree, Random Forest etc

04Classification

Know all about Logistic Regression, K-NN Intuition & Code , Naive Bayes, Decision Tree Intuition, Decision Tree code, Random Forest Code, etc

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Reviews and Ratings

Vidit Saini
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Reviews and Ratings

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Gudipati Sai Krishna
Placed in Software Developer at Qualcomm
I recently completed a machine learning course and it was an incredibly valuable and enriching experience. The course material was well-organized and easy to follow, and the instructor was knowledgeable and always available to answer questions. I particularly appreciated the hands-on projects and the opportunity to apply what I learned to real-world situations. I feel much more confident in my ability to utilize machine learning techniques in my work and I would highly recommend this course to anyone looking to gain a solid understanding of the field.
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Manoj Sahit Reddy Vanga
Intern in Sciffer analytics
The course is very broad covering topics from basic to some advanced machine learning topics. It is also very practical oriented.
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Mandavyapuram Hemanth Kumar
Placed in Accenture as a Advance Application Developer
This course is very useful for a Beginner who is passionate about Machine Learning. This Course contains Detail explanation from the scratch. With the help of this Course, I can make myself a few mini projects which are very useful before attending Campus interviews.
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Samarjeet Banik
Placed in Ernst & Young
This course is well-structured. After this course, I got exposure to real-world problems related to ML and I was able to apply the learnings. Even though I took the self-paced course, I was able to complete the course on time because GFG provided assistance and planner for that. The track questions and contests are the real attraction of this course. They really help you push forward in applying the learnings.
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Adesh Pawar
Placed at Rockwell Automation
First of all, I want to thank GFG for providing such as amazing course, I personally learned a lot of things and this helped me with getting my placement and I wanna thank GFG team for creating such an informative course.
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Vidit Saini
Placed at Outlier
"With the completion of the Geeksforgeeks Machine Learning - Basic to Advanced course, I am successful in building a solid foundation in Machine Learning. This detailed course covered a wide variety of topics, from fundamental concepts of machine learning to complex algorithms and techniques. I started from basics—like understanding of ML concepts, and data wrangling, and then learned statistical analysis—which provided a solid base for going ahead for more advanced material. As the course progressed through different machine learning algorithms, such as ensemble methods, linear regression, classification, and clustering, I gained a deep understanding of how various models work and when to use them. The various hands-on projects, which included data analysis and predictive modeling, gradually enhanced my real-world problem-solving skills. Furthermore, the focus on feature engineering and this type of project-based learning has improved my ability to apply theoretical knowledge in practical situations, making me skilled at handling distinctive ML tasks. Overall, this course has given me a strong grasp of machine learning principles, prepared me for further advanced studies on Deep Learning and enhanced my practical analysis skills in this field."

Frequently Asked Questions

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Is there any number to contact for any query?

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Is this a certification course?

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How can I register for the course?

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Is there any demo lecture video of this course?

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Do we have doubt support in this program?

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What features does Doubt Support have?