• No products in the cart.

This course is designed for individuals who are interested in learning the basics of machine learning with Python. The course covers various topics and makes difficult concepts very easy to understand. It includes multiple practical case studies to help you gain hands-on experience in implementing machine learning algorithms.

Session 1: Basic Statistics The first session covers the fundamental concepts of statistics, including mean, median, mode, standard deviation, and variance. These concepts are essential for understanding machine learning algorithms and their outputs.

Session 2: Data Exploration Validation Cleaning In this session, you will learn how to explore and validate your data. You will also learn how to clean your data by removing missing values, handling outliers, and dealing with imbalanced data.

Session 3: Projects Initiation The third session is dedicated to initiating projects. You will learn how to identify business problems, formulate problem statements, and develop project plans.

Session 4: Regression Analysis The fourth session covers regression analysis, including linear regression, multiple regression, and polynomial regression. You will learn how to build regression models and interpret their results.

Session 5: Logistic Regression The fifth session covers logistic regression, which is used for classification problems. You will learn how to build logistic regression models and interpret their results.

Session 6: Project Phase 2 – Simple ML Model In this session, you will implement a simple machine learning model to solve a business problem. You will learn how to preprocess the data, split it into training and testing sets, and build a machine learning model.

Session 7: Decision Trees The seventh session covers decision trees, which are used for classification and regression problems. You will learn how to build decision tree models and interpret their results.

Session 8: Model Selection Cross Validation In this session, you will learn how to select the best machine learning model for your data. You will also learn how to perform cross-validation to assess the performance of your models.

Session 9: Feature Engineering The ninth session covers feature engineering, which involves selecting and transforming the features of your data to improve the performance of your machine learning models.

Session 10: Project Phase 3 In this session, you will implement feature engineering and model selection techniques

Session 11: Random Forest The eleventh session covers random forest, which is an ensemble learning method used for classification and regression problems. You will learn how to build random forest models and interpret their results.

Session 12: Boosting The twelfth session covers boosting, which is another ensemble learning method used for classification and regression problems. You will learn how to build boosting models and interpret their results.

Session 13: Project Phase 4 In this session, you will implement advanced ML models like Random Forest and Boosting

Session 14: NLP Data Preprocessing The fourteenth session covers NLP data preprocessing, which involves cleaning and transforming text data for use in machine learning algorithms.

Session 15: Sentiment Analysis The fifteenth session covers sentiment analysis, which is a natural language processing technique used to determine the sentiment of a piece of text.

Session 16: Testing Of Hypothesis The final session covers hypothesis testing, which is used to determine whether a hypothesis about a population is true based on a sample of data.

In conclusion, this course covers a broad range of machine learning topics and provides practical case studies to reinforce your learning. The course is designed to be one of the best in the industry, and it makes difficult concepts very easy to understand.

Course Reviews


33 ratings
  • 5 stars28
  • 4 stars5
  • 3 stars0
  • 2 stars0
  • 1 stars0
  1. fundamental and advanced concepts


    The course is a comprehensive program that teaches fundamental and advanced concepts in an easily understandable manner for individuals without a math or engineering background. The course provides extensive knowledge and an opportunity to apply concepts learned in a final project. I gained a significant amount of knowledge and experience through the course.

  2. One of the best online courses


    It is very good. We have data set for practice. Good coverage of all the topics and quiz. Team used simple words. This is by far one of the Best online courses, I ever had.

  3. Good content but delivery could be better.


    I recently took a Machine Learning course at Statinfer. While I found the content to be good, the delivery lacked engagement. Improvements could be made with better video transitions and an overview of topics to be covered. Overall, it has the potential to be a great course with a few tweaks.

  4. great content


    The data science course was an exceptional experience, as the instructors exuded a profound passion and a comprehensive grasp of the subject matter. The course provided comprehensive coverage of all the essential topics necessary for success in the field of data science, including programming in Python, machine learning, and data visualization. The instructors were exceptional in presenting the concepts and their practical applications, utilizing real-world data examples and problems to aid the learning process. The course was designed to provide an all-encompassing and hands-on learning experience, ensuring students are well-equipped with the necessary skills and knowledge to excel in the field of data science.

  5. Enjoyed it


    This course was fantastic! I thoroughly enjoyed it. The instructor was perfect for the job, as they were adept at explaining complex concepts in a clear manner. Additionally, the examples and cases selected were engaging and thought-provoking. Overall, it was a wonderful learning experience, and I highly recommend this course to anyone interested in the subject matter.

  6. Excellent Machine Learning Course at Statinfer


    The course provided a data set for practice, which helped me to apply the concepts taught in the lectures.

    The course covered all the necessary topics and included quizzes to test my understanding. I appreciated how the team used simple language to explain complex ideas.

    While the only input I have is to improve the audio quality for some classes, overall, this was one of the best online courses I have taken. Thank you for providing such a nice course.

  7. Fantastic course


    This course is fantastic. He teaches everything you need to know about Logistic Regression and its applications. Overall, it’s been a fantastic resource to learn about machine learning,

  8. Totally worth it


    Totally worth it. Valuable for machine learning and deep learning beginners. Learned lots of stuffs. I can now use machine learning on my job. Thank you!!!

  9. Real time coding


    I liked how the author does coding in real-time, making errors and explaining what causes them and how to correct them.

    Good course for people with programming experience, like me. Some calculus equations hop over steps but it is possible to make it by yourself using a formula sheet.

  10. selected material


    This course is truly exceptional, thanks to the outstanding instructor and carefully selected material that includes numerous practical exercises and illustrative examples. I thoroughly enjoyed the experience and gained valuable insights from it. The instructor’s teaching style was superb, and I plan to enroll in more of their courses in the future.

  11. Appreciated...


    This course has been a game-changer for me in terms of understanding the fundamentals of machine learning. Unlike other courses that merely focus on coding and using libraries, this course delves into the underlying concepts, which I consider the most crucial aspect of this field. It has helped me to gain a firm grasp of many fundamental concepts in machine learning that I struggled with before. I appreciate the instructor’s approach, which emphasizes understanding the theory before moving on to the practical aspects. Overall, I highly recommend this course to anyone looking to gain a deeper understanding of machine learning.

  12. Informative


    Find this course to be incredibly engaging and informative, and I am grateful for the opportunity to learn from it. The knowledge and skills I have gained from this course will undoubtedly be beneficial as I pursue my goal of becoming a data analyst. I appreciate the efforts of the entire team for putting together such an outstanding course. Thank you in advance for your continued support as I embark on this new career path. I look forward to putting everything I have learned into practice..

  13. Excellent course.


    This course exceeded my expectations! I must say, I haven’t mastered all the concepts, but it has put me on the right path. The course design is thoughtful and well-structured, making it easy to understand and follow along. I commend the instructor for delivering such an excellent course.

  14. Teaches actual machine learning


    This course is dense with high quality content. It teachs you actual Machine Learning, not Machine Learning API usage and data preprocessing like most other courses.

  15. Easy to grasp


    This course is incredibly comprehensive, covering all the essential aspects of SQL, from basic concepts to more advanced topics. What’s impressive about this course is that it has been designed to make it accessible to non-math and non-engineering students, by presenting the content in a simple and understandable manner. The teaching style is very effective, making even complex topics easy to grasp.

    Throughout the course, I gained a lot of valuable knowledge, and I appreciated the way that the instructor presented everything in an organized and logical way. The final project was an excellent way to bring everything together and apply what we had learned in a practical context. Overall, I found this course to be an excellent resource for anyone wanting to learn SQL, regardless of their background or prior experience.

  16. Combining theory and programming


    I found that is an excellent idea to combine brief theoretical insights with programming. This allows each user to understand and build their own models and then compare their results with those obtained with different specialized libraries

  17. Easy to understand


    Statinfer teaches in a simple way where every one can understand…Assignments helps a lot to learn the subject.. Simple way of phyrton learns in Statinfer only…

  18. Cheers!


    I thoroughly enjoyed this course, and I feel fortunate to have completed it. The tutorials provided a great mix of intuition and practical applications, which helped me learn a lot. Kiril.Statinfer simplified complex concepts to the point where even a child could understand, and I cannot thank them enough for that. I am grateful to have had the opportunity to learn from Statinfer and I look forward to taking more courses from them in the future. Cheers!

  19. Well in-depth content


    Amazing lectures with in-depth content. The Instructor makes us traverse the route of investigative study to understand concepts and he is there to rescue in Q/A if we hit a roadblock.

  20. clear explanations


    The course covered a broad range of topics, from basic machine learning algorithms to advanced techniques such as neural networks and deep learning. The instructor was knowledgeable and provided clear explanations, and the content was well-structured and easy to follow. I appreciated the numerous hands-on exercises and projects, which allowed me to apply the concepts I learned in practice.

  21. Thank you


    It is really good. I could actually use what I have learned at work. However, I would really love here from homework and assessments to be given out to better my skill,,..

  22. Fortunate to have


    I feel fortunate to have had access to such an excellent resource at such an affordable price. The course provides a comprehensive introduction to the field of machine learning, covering all the essential topics and skills needed to get started. The content is presented in a clear and engaging way, making it easy to follow along and understand.

  23. Necessary to all


    This is an exceptional course suitable for both beginners and intermediate level learners in machine learning. It offers a comprehensive understanding of the subject, providing a strong foundation for learners. The course is highly recommended, as it covers all the necessary aspects of machine learning, making it a complete package.

  24. 4

    This course provided valuable insights and maintained a well-paced learning experience. The ideas were explained in a manner that was easy to understand and grasp



    Good start to gain knowledge about ML.

  26. 5

    To improve the basics it is very helpful

  27. 5

    it is very use full and good teaching

  28. many thanks


    very useful for the beginers plese go a head

  29. 5

    Teaching skills are good. Sometimes teaching very fastly, may be some students can’t understood

  30. 5

    This course is really helpful and easy to understand.



    This ML course was very easy to learn and it may helpful to my bright future.

  • 7,999
  • Course Badge


Statinfer derived from Statistical inference. We provide training in various Data Analytics and Data Science courses and assist candidates in securing placements.

Contact Us


+91- 9676098897

+91- 9494762485


Our Social Links

© 2020. All Rights Reserved.