Machine Learning is the most popular field in computer science in recent times. It is one of the emerging technologies with many organizations in various sectors embracing it. if you are a working professional or student, it doesn’t matter, there are several online courses on platforms such as edX, Coursera, Udemy, etc. from the top universities.
You can learn the basics of Machine Learning and then implement those concepts in your projects. These courses can be a great stepping stone for you if you are looking for a career in the software industry. Most popular courses do not come free, will consists of certain amount as payment. Here’s some of the popular courses on machine learning:
1. Basic Machine Learning by Stanford University Via Coursera
This is the most famous Machine Learning course available on the internet, held by Andrew Ng, the former Chief Scientist for Baidu. This Machine Learning course covers Linear Regression with One Variable, Support Vector Machines, Linear Regression with Multiple Variables, Logistic Regression, Neural Networks, Regularization, Unsupervised Learning, etc. that you can learn using Octave or MATLAB or any python platform. This course can be completed in 11 weeks and it covers various aspects and applications of Machine Learning. After completing this course, you will attain a Shareable Certificate that you can show on your resume or LinkedIn profile.
2. Deep Learning Specialization by deeplearning.ai via Coursera
This is an advanced specialization for Deep Learning offered by Andrew Ng after you complete the basic Machine Learning course. This will give you more about deep learning with topics like long short-term memory (LSTM), Convolutional networks, Recurrent neural networks, Natural Language Processing, etc. This course also offers personal stories and career advice from several top leaders in Deep Learning that will enrich your career. This Deep Learning specialization consists of 5 courses including Neural Networks and Deep Learning, Improving Deep Neural Networks, Structuring Machine Learning Projects, Convolutional Neural Networks, and Sequence Models. You will also develop deep learning models in several different fields like autonomous driving, healthcare, natural language processing, music generation, etc. After completing this course, you will attain a Shareable Certificate that you can show on your resume or LinkedIn profile.
3. Machine Learning for Data Science and Analytics by ColumbiaX Via edX
This course by Columbia will give you deep knowledge on the fundamentals of Machine Learning and its different algorithms. It will allow you to attain solutions for real-world problems using predictive analytics by understanding the principles of Machine Learning. This course will focus on Machine Learning algorithms such as Logistic Regression, Support Vector Machines, Unsupervised Learning, Linear Regression with One Variable, Linear Regression with Multiple Variables, etc. as well as to develop data predictions by data analysis and using topic modeling to find the hidden meaning in large amounts of data. At the end of this course, you will attain an instructor-signed certificate from edX and ColumbiaX to demonstrate your knowledge of Machine Learning for Data Science and analytics.
4. Machine Learning with Python by IBM (edX)
This course will make you understand the Machine Learning concept using Python. You will study the basics of Machine Learning using Python and transform this theoretical knowledge into practical skills. This course is divided into duration of five weeks with each of them focusing on an Introduction to Machine Learning, Regression algorithms involving Linear, Non-linear, and Model evaluation methods, Classification algorithms including K-Nearest Neighbour, Logistic Regression, Decision Trees, Support Vector Machines, etc., Unsupervised Learning involving Hierarchical Clustering, K-Means Clustering, Density-Based Clustering and Recommender systems. Candidates will attain an instructor-signed certificate from edX and IBM to demonstrate your knowledge of Machine Learning using Python.
5. Hands-On Python & R In Data Science (Udemy)
This course focuses the basics of Machine Learning and Data Science from A-Z. This course is perfect for candidates who want to learn Machine Learning and Data Science to make a career in these fields. This course teaches machine learning on both Python and R with a focus on more specific topics such as Reinforcement Learning, Deep Learning, Natural Language Processing, etc. This course consists of content structure with topics such as Clustering, Data Preprocessing, Regression, Classification, Association Rule Learning, Reinforcement Learning, Natural Language Processing, Deep Learning, Dimensionality Reduction, and Model Selection & Boosting. After completing the course, you will attain a certificate of completion that you can show on your CV, LinkedIn profile, etc.
Candidates can choose the platform of their wish as all platforms are equally, however it is more important to learn basic concepts of machine learning as it is a technology that is being implemented in various industry and growing exponentially. Hence, learning these concepts will help candidates in their careers.
