Course Information
Course Overview
Build a Portfolio/Resume of Machine Learning projects in Python and get a job of Data Scientist/ ML Engineer
This is the first course that gives hands-on Machine Learning Projects using Python..
Student Testimonials:
Another great course! Real world data, various data manipulations techniques, practical visualizations and insights, useful ways of automation. I've learnt a lot in a short period of time. Solid 5 stars! Thanks - Sebastian Suminski
Very clear and understood explanation using case study. It was very clear showing the beauty of the function and the visualization when he used according to the case study. Thanks - Sadik
The course is really good and practical. The explanation right to the point. Definitely recommended for who learned the theory and want to do hands- on - Deepthi kiran Chebrolu
Excellent Course and amazing work @shan singh sir I am glad to be your student one small suggestion is try to show the deployment phase like showing our end project for others using flask, streamlit, gradio etc It will help lot of us to learn about the UI and deployment as well. - Veluturi Sunil Tagore
Sir this is amazing i have completed a little bit remaining this is so much adorable thank you to completing my project in ml - Jay Kumar Vagairya
Machine Learning is one of the hottest technology field in the world right now! This field is exploding with opportunities and career prospects. Machine Learning techniques are widely used in several sectors now a days such as banking, healthcare, finance, education transportation and technology.
This course covers several technique in a practical manner, the projects include coding sessions as well as Algorithm Intuition:
So, if you’ve ever wanted to play a role in the future of technology development, then here’s your chance to get started with Machine Learning. Because in a practical life, machine learning seems to be complex and tough,thats why we’ve designed a course to help break it down into real world use-cases that are easier to understand.
1.. Task #1 @Predicting the Hotel booking : Predict Whether Hotel booking is going to cancel or not
3.. Task #2 @Predict Whether Person has a Chronic Disease or not : Develop a Machine learning Model that predicts whether person has Chronic kidney disease or not
2.. Task #3 @Predict the Prices of Flight : Predict the prices of Flight using Regression & Ensemble Algorithms..
The course covers a number of different machine learning algorithms such as Regression and Classification algorithms. From there you will learn how to incorporate these algorithms into actual projects so you can see how they work in action! But, that’s not all. In addition to quizzes that you’ll find at the end of each section, the course also includes a 3 brand new projects that can help you experience the power of Machine Learning using real-world examples!
Course Content
- 7 section(s)
- 81 lecture(s)
- Section 1 Intro to this course
- Section 2 Introduction to Machine Learning
- Section 3 Introduction to Life-Cycle of Machine Learning Project
- Section 4 Project 1-->> Predict the cancellation of Hotel Booking
- Section 5 Project 2-->> Predict status of Chronic kidney disease (Health care Case-study )
- Section 6 Project 3-->> Predict Prices of Flights Tickets ( Airline Case-study )
- Section 7 Bonus Section
What You’ll Learn
- Machine Learning Engineers earn on average $164,000 - become Job Ready ML Engineer with this course!
- Go from zero to hero in Entire Pipeline of Machine learning from Data Collection to building a Machine Learning Model
- Solve any problem in your business, job or in real-time with powerful Machine Learning algorithms
- Mathematics behind All Machine Learning algos ( Linear Regression , logistic , Decision Tree , Ensemble algos , KNN , Naive Bayes & many more !
- Various Feature selection Techniques & how to apply it in Real-World
- How to Approach a problem in Real-world..
- Case studies
Skills covered in this course
Reviews
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VValentin Mesaros
Quite good material. But, quite bad English. Moreover, when the oral English was bad, the presentation slides contained spelling mistakes... e.g., when the hamming distance was introduced ---> big deception point
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AArvind Muthusamy
USefull
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EEmily House
The information is very practical. It's great for tips on how to use Python for data analysis. It's not as structured as some other courses and it's a bit difficult to understand sometimes, but lots of great Python tips.
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TTrayamb Rathore
Instructor don't seem to have knowledge, also lacks communication and is not able to explain the things clearly. the course mentions it contains the portfolio project but this are some very simple project here which does not involve any complexity and I doubt if anyone would write such projects in their cv. expected better from udemy, please keep a quality check on the content.