There are plenty of courses / certifications accessible to self-start your career in Machine Learning.These courses are given in online or offline. The main trouble students face is to choose the best out of these courses.
How to choose the Right Online Course for you?
Choosing the right course is always a difficult task for any individual.
So I have selected all these Courses based on some basic Criteria:
- Course Content/Description
- Course Quality,
- Cost,
- Instructor
- Career Opportunities,
- Highest Reviewed,
- Best Sellers,
- Highest Rated,
- Newest etc
For most of these Courses you will Get :
1.) Full lifetime access
2.) Access on mobile and TV
3.) Certificate of Completion
4.) 30-Day Money-Back Guarantee
With the introduction of few newly introduced courses, it has turned out to be considerably more hard to make a right decision. The dread of putting in unworthy courses keeps to remain the greatest obstacle for students.
So below are the list of the Top 10 Best Advanced Machine Learning Courses, Training program accessible online in 2018 to enable you Learn Machine Learning. These are best for Specialists.
If you are a beginner I would suggest to go through my previous article Best Global Machine Learning Certifications & Training.
1.) Advanced Machine Learning Specialization
This specialization gives an introduction to deep learning, reinforcement learning, natural language understanding, computer vision and Bayesian methods. Top Kaggle machine learning practitioners and CERN scientists will share their experience of solving real-world problems and help you to fill the gaps between theory and practice.
Upon completion of 7 courses you will be able to apply modern machine learning methods in enterprise and understand the caveats of real-world data and settings.
Course Rating: Newest, Highest Rated 4.5 & Up, Most Reviewed, Best Price
Course Link :CLICK HERE for the Special Offer
2.) Artificial Intelligence: Advanced Machine Learning
In this course, you will work through various examples on advanced algorithms, and focus a bit more on some visualization options. We’ll show you how to use random forest to predict what type of insurance a patient has based on their treatment and you will get an overview of how to use random forest/decision tree and examine the model.
And then, we’ll walk you through the next example on letter recognition, where you will train a program to recognize letters using a support Vector machine, examine the results, and plot a confusion matrix.
Course Rating: Newest, Highest Rated 4.5 & Up, Most Reviewed, Best Price
Course Link :CLICK HERE for the Special Offer
3.) Advanced Machine Learning and Signal Processing
This course is part of the IBM Advanced Data Science Specialization which IBM is currently creating and gives you easy access to the invaluable insights into Supervised and Unsupervised Machine Learning Models used by experts in many field relevant disciplines.
You’ll learn about the fundamentals of Linear Algebra to understand how machine learning modes work.
If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge.
Course Rating: Newest, Highest Rated 4.5 & Up, Most Reviewed, Best Price
Course Link :CLICK HERE for the Special Offer
4.) LEARNING PATH: Python: Advanced Machine Learning with Python
The highlights of this Course are:
- Solve interesting, real-world problems using machine learning and Python as the learning journey unfolds
- Use Python to visualize data spread across multiple dimensions and extract useful features
This Learning Path is your entry point to machine learning. It starts with an introduction to machine learning and Python language.
You’ll learn the important concepts such as exploratory data analysis, data preprocessing, feature extraction, data visualization and clustering, classification, regression, and model performance evaluation.
Course Rating: Newest, Highest Rated 4.5 & Up, Most Reviewed, Best Price
Course Link :CLICK HERE for the Special Offer
5.) Machine Learning with TensorFlow on Google Cloud Platform Specialization
In this course you will learn how to write distributed machine learning models that scale in Tensorflow, scale out the training of those models. and offer high-performance predictions. Convert raw data to features in a way that allows ML to learn important characteristics from the data and bring human insight to bear on the problem.
Finally, learn how to incorporate the right mix of parameters that yields accurate, generalized models and knowledge of the theory to solve specific types of ML problems. You will experiment with end-to-end ML, starting from building an ML-focused strategy and progressing into model training, optimization, and productionalization with hands-on labs using Google Cloud Platform.
Course Rating: Newest, Highest Rated 4.5 & Up, Most Reviewed, Best Price
Course Link :CLICK HERE for the Special Offer
5.) Projects in Machine Learning : Beginner To Professional
The course will start at the very beginning and delve right into machine learning, before breaking down the most important concepts principles.
Projects That Are Included in This Course:
- Project 1 – Breast Cancer Detection – In this project, you’ll learn to use the K-nearest neighbor algorithm to help detect breast cancer malignancies by using a support vector machine.
- Project 2 – Board Game Review Prediction – In this project, you’ll see how to perform a linear regression analysis by predicting the average reviews on a board game in this project.
- Project 3 – Credit Card Fraud Detection – In this project, you’ll learn to focus on anomaly detection by using probability densities to detect credit card fraud.
- Project 4 – Stock Market Clustering – Learn how to use the K-means clustering algorithm to find related companies by finding correlations among stock market movements over a given time span.
- Project 5 – Diabetes Onset Detection – You’ll learn how to fine-tune a deep learning neural network by performing a grid search to detect the onset of diabetes based on patient data.
- Project 6 – Markov Models and K-Nearest Neighbor Approaches to Classifying DNA Sequences –Learn about bioinformatics by using Markov models and K-nearest neighbor (KNN) algorithms in this project.
- Project 7 – Getting Started with Natural Language Processing In Python – This project will focus on Natural Language Processing (NLP) methodology, such as tokenizing words and sentences, part of speech identification and tagging, and phrase chunking.
- Project 8 – Obtaining Near State-of-the-Art Performance on Object Recognition Tasks Using Deep Learning – In this project, will use the CIFAR-10 object recognition dataset as a benchmark to implement a recently published deep neural network.
Course Rating: Newest, Highest Rated 4.5 & Up, Most Reviewed, Best Price
Course Link :CLICK HERE for the Special Offer
6.) Applied machine learning for Everyone
This course addresses “advanced beginners” and is all about executing machine learning in python. It covers some theory along the way but mostly focus on applying it.
If you want to start in machine learning I would recommend checking out my course “Machine learning for Beginners” first, since it covers more basics. However it is not mandatory.
Note that all the courses require to understand at least some basics of machine learning and are hands on practical coding courses. If that’s your way of learning it, than this course is for you!
Course Rating: Newest, Highest Rated 4.5 & Up, Most Reviewed, Best Price
Course Link :CLICK HERE for the Special Offer
7.) Machine Learning using Advanced Algorithms and Visualization
In this course, you will work through various examples on advanced algorithms, and focus a bit more on some visualization options. We’ll start by showing you how to use random forest to predict what type of insurance a patient has based on their treatment and you will get an overview of how to use random forest/decision tree and examine the model.
Finally, you’ll dive into the last example of predicting a movie genre based on its title, where you will use the tm package and learn some techniques for working with text data.
Course Rating: Newest, Highest Rated 4.5 & Up, Most Reviewed, Best Price
Course Link :CLICK HERE for the Special Offer
7.) Machine Learning for OpenCV 3 – Advanced Methods
Computer vision is one of today’s most exciting application fields of Machine Learning, From self-driving cars to medical diagnosis, computer vision has been widely used in various domains.
This course will cover essential concepts such as classifiers and clustering and will also help you get acquainted with neural networks and Deep Learning to address real-world problems.
The course will also guide you through creating custom graphs and visualizations, and show you how to go from raw data to beautiful visualizations. By the end of this course, you will be ready to create your own ML system and will also be able to take on your own machine learning problems.
Course Rating: Newest, Highest Rated 4.5 & Up, Most Reviewed, Best Price
Course Link :CLICK HERE for the Special Offer
8.) AWS Machine Learning, AI, SageMaker – With Python
In this course, you will learn AI and Machine Learning in three different ways:
AWS Machine Learning
AWS Machine Learning Service is designed for complete beginners.
You will gain hands-on knowledge on complete lifecycle – from model development, measuring quality, tuning, and integration with your application
AWS SageMaker
The next service is AWS SageMaker.
If you are comfortable coding in Python, SageMaker service is for you.
Application Services
In Application Services section of this course,
You will learn about a set of pre-trained services that you can directly integrate with your application.
Course Rating: Newest, Highest Rated 4.5 & Up, Most Reviewed, Best Price
Course Link :CLICK HERE for the Special Offer
8.) Beginner to Advanced Guide on Machine Learning with R Tool
This course is intended for both freshers and experienced hoping to make the bounce to Data Science.
R is a statistical programming language which provides tools to analyze data and for creating high-level graphics.
The topic of Machine Learning is getting exceptionally hot these days in light of the fact that these learning algorithms can be utilized as a part of a few fields from software engineering to venture managing an account.
Students, at the end of this course, will be technically sound in the basics and the advanced concepts of Machine Learning.
Course Rating: Newest, Highest Rated 4.5 & Up, Most Reviewed, Best Price
Course Link :CLICK HERE for the Special Offer
9.) Make predictions with Python machine learning for apps
This course is for People who want to learn machine learning concepts through practical projects with PyCharm, Python, Android Studio, Java, and TensorFlow. Anyone who wants to learn the technology that is shaping how we interact with the world around us.
Anyone who is interested in predictive modeling for handling the stock market, weather, and text.
Course Rating: Newest, Highest Rated 4.5 & Up, Most Reviewed, Best Price
Course Link :CLICK HERE for the Special Offer
10.) CoreML – Master Machine Learning for iOS Apps
This course is for If you are an intermediate to advanced iOS developer looking to add more skills under your belt.
- If you are looking to quickly get up to date with the latest iOS 11 APIs.
- If you are a beginner and want to learn to create intelligent iOS apps using machine learning without having to understand a lot of complicated maths.
Course Rating: Newest, Highest Rated 4.5 & Up, Most Reviewed, Best Price
Course Link :CLICK HERE for the Special Offer
FINAL WORDS
Since every one of these courses can be done on the web, you have the advantage of carrying on gaining from pretty much anyplace on the planet.
PS: Start taking these Best courses listed above. Perhaps, a $5-10 course can change your Career for eternity. Invest Now and Reap Rewards later with Compounding.
Good Luck!
