If you're interested in machine learning and want to learn how to build powerful machine learning models to solve real-life problems, then the Complete Machine Learning Course with Python is the perfect course for you to take. With endorsements from thousands of students and an average rating of 4.39572, this highly-rated course will teach you everything you need to know about machine learning with Python.
The Course Content
The course is led by Anthony NG, a senior lecturer based in Singapore, who follows a project-based teaching style. You’ll start by learning the fundamental concepts of machine learning, before moving on to more advanced topics and even building up your own portfolio of twelve machine learning projects. By the end of the course, you'll be a machine learning engineer, with the skills to tackle the most complex real-world problems that require machine learning algorithms to solve.
The course is packed with over 18 hours of video content, and thousands of students have already given it their seal of approval, citing the course's thoroughness and project-based approach. One of the best parts about this course is that you don't need any prior machine learning experience or even Python knowledge to enroll. Anthony Ng goes through all the algorithms and code step-by-step, so you can easily follow along and learn machine learning in a stress-free way.
The Updated and Improved Course Content
As of November 2019, the Complete Machine Learning Course with Python has undergone a complete overhaul. With updated and improved content, the course covers everything you need to master machine learning in one place.
The new material covers:
- The foundations of deep learning, including classical programming versus machine learning, how to differentiate between machine and deep learning, neural networks, tensor operations, classification of machine learning, and advanced concepts like overfitting, underfitting, dropout, validation, and testing.
- Computer vision with convolutional neural networks that cover topics like building layers, understanding filters and kernels, transfer learning, and feature extraction.
On top of that, the older content has also been improved and updated. You'll learn about binary and multi-class classifications with deep learning, the use of unsupervised machine learning algorithms such as hierarchical clustering and k-means clustering, how to use support vector machines for handwriting recognition and general classification problems, and even advanced topics like association rules and predicting staff attrition.
The Benefits of Taking the Course
The average salary of a machine learning engineer in the US is around $166,000. And by taking this course, you'll have the tools to solve real-life problems and build a solid machine learning portfolio that can help you land your dream job. You'll learn how to use tools like Matplotlib and Seaborn to communicate effectively with data, employ unsupervised and supervised machine learning algorithms, use decision trees to make accurate predictions, engineer better features for better predictions, and so much more.
You'll also be able to do all this without prior machine learning experience or even Python experience. Anthony Ng makes every coding step so easy to follow that all you need is a basic understanding of coding and you'll be good to go.
The Verdict
In short, the Complete Machine Learning Course with Python is an excellent course for anyone interested in machine learning. With its updated and improved content, easy-to-follow coding mastery, and project-based approach, you'll leave the course a confident machine learning engineer with skills you can apply to real-life data problems.
If you’re serious about elevating your career or making a start in machine learning, this course will get you to where you want to go.
