5 Best Machine Learning Courses Online

5 Best Machine Learning Courses Online :- Machine Learning is the application of artificial intelligence. Machine learning has many types of algorithms. Every algorithm differs. Algorithm learn a mapping of input to output.

In today’s world of Machine Learning there is too much demand and In this field has number of jobs. One reason for this is that people like it. These courses are for those who want to start learning Machine Learning or interesting in it. Also for those who know the basics of machine learning but learn to more about it and explore all the different fields of Machine Learning. Students are studying in college, they want to make career in Data Science. Those people are not satisfied with their job and want to become a Data Scientist. These courses are for those.

Now, these are the 5 best Machine Learning courses :-

1. Machine Learning A-Z: Hands-on Python & R in Data Science :-

This course will teach you. How you will create Machine learning algorithms in Python and R.

However, the course is with practical exercise who are based on real-life examples. You will learn the theory as well as you will also get some hands-on practice building your own models.

And this course includes both Python and R code templates who you can download and use on your own projects. This course will teach you :

Master Machine Learning on Python & R
Great intuition of Machine Learning models
Make accurate predictions, powerful analysis, and robust Machine Learning models
Create strong added value to your business
Use Machine Learning for personal purpose
Handle specific topics like Reinforcement Learning and Deep Learning
Handle advanced techniques like Dimensionality Reduction
Understand Machine Learning model to choose for each type of problem

This online course has 294 lectures. To know more about detail view on it.

The course instructors are Mr. Kirill Eremenko and Mr. Hadelin de Ponteves.

Mr. Kirill Eremenko is the Data Science management instructor with experience about five years in finance, retail, transport. He is public speaker and he is regularly present on Big data at leading Australian Universities and other events. Mr. Kirill Eremenko share his real life experience and academic background in Physics and Mathematics to deliver professional step by step coaching in the Data Science.
Mr. Hadelin de Ponteves have appeared Engineering master’s degree with a specialisation in Data Science. He is also entrepreneur. He has work experience at Google where he implemented some Machine Learning models for business analytics.

This course has 4.5(93,172) rating and 462250 students enrolled with it. The specialty of this course is, it is provide with seven different languages. You can easily learn this with your own choice of language.It has 31 articles, 5 downloadable resources and full lifetime access. You can access this course on mobile and television.

2. Python For Data Science and Machine Learning Bootcamp:-

This course instructor is Jose Marcial Portilla. He has years of experience in Data Science and programming and also trainer in the same field. He use his experience in teaching and data science to help other people learn the power of programming. Recently, he also works as the Head of Data Science for Pierian Data Inc.

It is really good course for beginners. It helps you started into the world of machine learning. The coding component of the course is great. This course skills provide a basic understanding. It is very well explained about the complete Visualization techniques with matplotLib, seaborn, ploty etc.

You will learn these followings topics :

Use Python for Data Science and Machine Learning
Use Spark for Big Data Analysis
Implement Machine Learning Algorithms
How to use NumPy for Numerical Data
Learn to use Pandas for Data Analysis
How to use Matplotlib for Python Plotting
Learn to use Seaborn for statistical plots
Use Plotly for interactive dynamic visualizations
Use SciKit-Learn for Machine Learning Tasks
K-Means Clustering
Logistic Regression
Linear Regression
Random Forest and Decision Trees
Natural Language Processing and Spam Filters
Neural Networks
Support Vector Machines

This course has 149 lectures:

Environment set up
Jupyter overview
Python crash course
Numpy – Python for Data Analysis
Pandas – Python for Data Analysis
Pandas Exercises – Python for Data Analysis
Matplotlib – Python for Data Visualization
Seaborn – Python for Data Visualization
Pandas Built in Data Visualization – Python for Data Visualization

Environment set up has 1 lecture, Jupyter overview has 3 lectures, Python crash course has 8 lectures, Python for Data Analysis-NumPy has 8 lectures, Python for Data Analysis-Pandas has 11 lectures for detail about more lectures view on it.

246,547 Students are already enrolled in this course. You can learn it by your language because this course teaches with 7 different languages. This course has 4.5 rating out of 5. Total 10 articles includes with it, 4 downloadable resources, full lifetime access, you can access it on mobile phone and television.

3. Machine Learning, Data Science and Deep Learning with Python :

This course is complete machine learning tutorial with data science, Tensorflow, artificial intelligence, and neural networks. Machine language and Artificial language are used in today’s world and this course is complete about that. In it, you will learn each concept in plain English and no any confusion in Mathematical notation. This course’s goal is on practical understanding and application of them. The course is easier, more straight forward and interesting. You will cover all topics step by step and the topics are in advance level.

You will cover these topics:-

Build artificial neural networks
Classify images, data using deep learning
Make predictions using linear regression, polynomial regression.
Data Visualization with MatPlotLib.
Why we use Implement machine learning at massive scale with Apache Spark’s MLLib
Understand reinforcement learning and how to build a Pac-Man bot
Using K-Means clustering, Support Vector Machines (SVM), KNN, Decision Trees, Naive Bayes, and PCA
How you will use train/test and K-Fold cross validation to choose and tune your models
Build a movie recommender system using item-based.
Clean your input data to remove outliers
Evaluate and design A/B tests using T-Tests and P-Values

What do you need to learn this course

You’ll need a desktop computer (Windows, Mac, or Linux). Some coding or scripting experience is required. High school level math skills will be required.

The course has total 101 lectures. The detail are :

Statics and Probability Refresher and python Practise have 13 lectures
Predictive Models have 4 lectures
Machine Learning with python has 15 lectures
Recommender Systems have 6 lectures
Data Mining and Machine Learning Techniques have 7 lectures
Dealing with real-world data has 6 lectures
Apache Spark: Machine learning on big data has 12 lectures
Experimental design /ML has 6 lectures
Deep learning and Neural networks have 16 lectures
Final projects has 2 lectures
3 lectures for you made it

Frank is the instructor of this course and he has worked in Amazon and IMDb, developing and managing technology. He has lots of data science experience, so he gives us real-world examples throughout the course. Frank has made a well-organized course.

This is the reason, 244,646 students are enrolled with it. Good reviews(58,939) taken by students. This course ratings is 4.5. Total 5 articles includes in the course, full lifetime access and also access on mobile and T.V. 13 hours on-demand videos include with this.

4. Data Science and Machine Learning Bootcamp with R :

This course instructor is Jose Marcial Portilla. He has years of experience as a professional instructor, also trainer for Data Science and programming. He has publications in various fields such as microfluidics, materials science, and data science technologies. Recently he works as the head of Data Science for Pierian Data Inc. Provides training in data science and python programming courses to employees working at top companies, including General Electric, Cigna.

This course will teach you how to use Data Science and Machine learning Bootcamp with R. In the course has full Knowledge about following topics :-

What the uses of program in R
How we can Use R for Data Analysis
learn how to create Data Visualizations
Uses of R to handle csv, excel, and SQL files.
Use R to manipulate data easily, R for Machine Learning Algorithms, and R for Data Science
Advanced Features of R
Use R Data Frames to solve complex tasks
Web scraping with R
Use ggplot2 for data visualizations and plotly for interactive visualizations
Machine Learning with R
Linear Regression
K Nearest Neighbors
K Means Clustering
Decision Trees
Random Forests
Data Mining Twitter
Learn Neural Nets and Deep Learning

To learn this course, you just need to have basic math skills and Computer Access with download privileges.

It has Total 127 lectures and the list is :

Mac OS installation set up
Linux installation
Introduction to R basics
Development Environment Overview
R Matrices, R Data Frames, R lists, and R Programming basics
Advanced R Programming
Data Input and Output with R (more view)

This course is for everyone whether it is student, employee or programmer. You can learn it by joining this.

The course rating is 4.6(8,426). 44,976 Student enrolled with this course. This course updated on September, 2019. Eight different languages used in the course, you can learn this course by your own language. Learn with enjoy.

5. Scala and Spark for Big Data and Machine Learning :

This course is the latest Data and Machine Technology. It has a Scala course that teaches step by step instead of assuming you know something similar like Java and giving tasks without properly introducing with it. This course covers basic and advance introduction how to apply it with Scala and Spark.

It has following topics that you will learn:-

How we can use Scala for Programming
Crash Course in Scala Programming
Use Spark to Process Large Datasets
Spark and Big Data Ecosystem Overview
Using Spark’s MLlib for Machine Learning
Scale up Spark jobs using Amazon Web Services
Learn how to use Databrick’s Big Data Platform

For learn this course you will require some skills :

Basic Programming Knowledge
Basic Math Skill
English Language

The course has 80 lectures, the detail are :-

Scala IDE options and overview
Window Scala and Spark Set-up and Installation
Mac OS Set-up and Installation
Linux Setup and Installation
Scala Programming : Level one
Collections
Scala Programming : Level two
Spark Dataframes with Scala
Introduction to Machine Learning (view more)

Each lecture will have two to five lectures.

The instructor of this course is Jose Marcial Portilla. He has many years of experience as a professional instructor and also trainer for Data Science and programming. Over the course of his career, he has developed a skill set in analyzing data and he use his experience in teaching. Recently, he works as the Head of Data Science for Pierian Data Inc.

The course rating is 4.4(3,672) and total 21,183 students enrolled with it. You will get the course with five different languages. Learn with your own choice language. Learn and enjoy the course.

It Includes 10 hours demand videos, 12 articles, 5 downloadable resources, full lifetime access, access on mobile and television also.