Data Science, Machine Learning, Deep Learning, and Artificial intelligence are really hot at this moment and offering a lucrative career to programmers with high pay and exciting work.
It’s a great opportunity for programmers who are willing to learn these new skills and upgrade themselves and want to solve some of the most interesting real-world problems.
It’s also important from the job perspective because Robots and Bots are getting smarter day by day, thanks to these technologies and most likely will take over some of the jobs which many programmers do today.
Hence, it’s important for software engineers and developers to upgrade themselves with these skills. Programmers with these skills are also commanding significantly higher salaries as data science is revolutionizing the world around us.
You might already know that the Machine learning specialist is one of the top paid technical jobs in the world. However, most developers and IT professionals are yet to learn this valuable set of skills.
For those, who don’t know what is a Data Science, Machine learning, or deep learning, they are very related terms with all pointing towards machine doing jobs which is only possible for humans till date and analyzing the huge set of data collected by modern day application.
Data Science, in particular, is a combination of concepts such as machine learning, visualization, data mining, programming, data mugging, etc.
There are a lot of popular scientific Python libraries such as Numpy, Scipy, Scikit-learn, Pandas, which is used by Data Scientist for analyzing data.
To be honest with you, I am also quite new to Data Science and Machine learning world but I have been spending some time from last year to understand this field and have done some research in terms of best resources to learn machine learning, data science, etc.
I am sharing all those resources in a series of a blog post like this. Earlier, I have shared some courses to learn TensorFlow, one of the most popular machine-learning library and today I’ll share some more to learn these technologies.
These are a combination of both free and paid resource which will help you to understand key data science concepts and become a Data Scientist. Btw, I’ll get paid if you happen to buy a course which is not free.
Here is my list of some of the best courses to learn Data Science, Machine learning, and deep learning using Python and R programming language. As I have said, Data Science and machine learning work very closely together, hence some of these courses also cover machine learning.
If you are still on fence with respect to choosing Python or R for machine learning, let me tell you that both Python and R are a great language for Data Analysis and have good APIs and library, hence I have included courses in both Python and R, you can choose the one you like.
I personally like Python because of its versatile usage, it’s the next best in my list of language after Java. I am already using it for writing scripts and other web stuff, so it was an easy choice for me. It has also got some excellent libraries like Sci-kit Learn and TensorFlow.
Data Science is also a combination of many skills e.g. visualization, data cleaning, data mining, etc and these courses provide a good overview of all these concepts and also presents a lot of useful tools which can help you in the real world.
Machine Learning by Andrew Ng
This is probably the most popular course to learn machine learning provided by Stanford University and Coursera, which also provides certification. You’ll be tested on each and every topic that you learn in this course, and based on the completion and the final score that you get, you’ll also be awarded the certificate.
This course is free but you need to pay for certificates, if you want. Though, it does provide value to you as a developer and gives you a good understanding of the mathematics behind all the machine learning algorithms that you come up with.
I personally really like this one. Andrew Ng takes you through the course using Octave, which is a good tool to test your algorithm before making it go live on your project.
1.Machine Learning A-Z: Hands-On Python and R — In Data Science
This is probably the best hands on course on Data Science and machine learning online. In this course, you will learn to create Machine Learning Algorithms in Python and R from two Data Science experts.
This is a great course for students and programmers who want to make a career in Data Science and also Data Analysts who want to level up in machine learning.
It’s also good for any intermediate level programmers who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning.
Data science is the practice of transforming data into knowledge, and R is one of the most popular programming language used by data scientists.
In this course, you’ll learn first learn about the practice of data science, the R programming language, and how they can be used to transform data into actionable insight.
Next, you’ll learn how to transform and clean your data, create and interpret descriptive statistics, data visualizations, and statistical models.
Finally, you’ll learn how to handle Big Data, make predictions using machine learning algorithms, and deploy R to production.
Btw, you would need a Pluralsight membership to get access this course, but if you don’t have one you can still check out this course by taking their 10-day free Pass, which provides 200 minutes of access to all of their courses for free.
3.** **Harvard Data Science Course
The course is a combination of various data science concepts such as machine learning, visualization, data mining, programming, data mugging, etc.
I suggest you complete the machine learning course on course before taking this course, as machine learning concepts such as PCA (dimensionality reduction), k-means and logistic regression are not covered in depth.
But remember, you have to invest a lot of time to complete this course, especially the homework exercises are very challenging
In short, if you are looking for an online course in data science(using Python), there is no better course than Harvard’s CS 109. You need some background in programming and knowledge of statistics to complete this course.
4. Want to be a Data Scientist? (FREE)
This is a great introductory course on what Data Scientist do and how you can become a data science professional. It’s also free and you can get it on Udemy.
If you have just heard about Data Science and excited about it but doesn’t know what it really means then this is the course you should attend first.
It’s a small course but packed with big punches. You will understand what Data Science is? Appreciate the work Data Scientists do on a daily basis and differentiate the various roles in Data Science and the skills needed to perform them.
You will also learn about the challenges Data Scientists face. In short, this course will give you all the knowledge to make a decision on whether Data Science is the right path for you or not.
5. Intro to Data Science by Udacity
This is another good Introductory course on Data science which is available for free on Udacity, another popular online course website.
In this course, you will learn about essential Data science concepts e.g. Data Manipulation, Data Analysis with Statistics and Machine Learning, Data Communication with Information Visualization, and Data at Scale while working with Big Data.
This is a free course and it’s also the first step towards a new career with the Data Analyst Nanodegree Program offered by Udacity.
6. Data Science Certification Training — R Programming
The is another good course to learn Data Science with R. In this course, you will not only learn R programming language but also get some hands-on experience with statistical modeling techniques.
The course has real-world examples of how analytics have been used to significantly improve a business or industry.
If you are interested in learning some practical analytic methods that don’t require a ton of maths background to understand, this is the course for you.
7. Intro To Data Science Course by Coursera
This course provides a broad introduction to various concepts of data science. The first programming exercise “Twitter Sentiment Analysis in Python” is both fun and challenging, where you analyze tons of twitter message to find out the sentiments e.g. negative, positive etc.
Btw, It’s not so good for beginners, especially if you don’t know Python and SQL but if you do and have a basic understanding of Data Science then this is a great course.
8. Python for Data Science and Machine Learning Bootcamp
There is no doubt that Python is probably the best language, apart from R for Data Analysis and that’s why it’s hugely popular among Data Scientists.
This course will teach you how to use all important Python scientific and machine learning libraries Tensorflow, NumPy, Pandas, Seaborn, Matplotlib, Plotly, Scikit-Learn, Machine Learning, and many more libraries which I have explained earlier in my list of useful machine learning libraries.
It’s a very comprehensive course and you will how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms!
9. Data Science A-Z: Real-Life Data Science Exercises Included
This is another great hands-on course on Data Science from Udemy. It promises to teach you Data Science step by step through real Analytics examples. Data Mining, Modeling, Tableau Visualization and more.
This course will give you so many practical exercises that the real world will seem like a piece of cake when you complete this course.
The homework exercises are also very thought-provoking and challenging. In short, If you love doing stuff then this is a course for you.
10. Data Science, Deep Learning and Machine Learning with Python
If you’ve got some programming or scripting experience, this course will teach you the techniques used by real data scientists and machine learning practitioners in the tech industry — and help you to become a data scientist.
The topics in this course come from an analysis of real requirements in data scientist job listings from the biggest tech employers, that makes it even more special and useful.
That’s all about some of the popular courses to learn Data Science. As I said, there is a lot of demand for good Data Analytics and there are not many developers out there to fulfill that demand.
It’s a great chance for the programmer, especially those who have good knowledge of maths and statistics to make a career in machine learning and Data analytics. You will be awarded exciting work and incredible pay.
Other useful Data Science and Machine Learning resources
Thanks, You made it to the end of the article … Good luck with your Data Science and Machine Learning journey! It’s certainly not going to be easy, but by following these courses, you are one step closer to becoming the Machine Learning Specialists you always wanted to be.
#data-science #machine-learning #deep-learning #python
Learn Data Science is this full tutorial course for absolute beginners. Data science is considered the “sexiest job of the 21st century.” You’ll learn the important elements of data science. You’ll be introduced to the principles, practices, and tools that make data science the powerful medium for critical insight in business and research. You’ll have a solid foundation for future learning and applications in your work. With data science, you can do what you want to do, and do it better. This course covers the foundations of data science, data sourcing, coding, mathematics, and statistics.
⭐️ Course Contents ⭐️
⌨️ Part 1: Data Science: An Introduction: Foundations of Data Science
⌨️ Part 2: Data Sourcing: Foundations of Data Science (1:39:46)
⌨️ Part 3: Coding (2:32:42)
⌨️ Part 4: Mathematics (4:01:09)
⌨️ Part 5: Statistics (4:44:03)
📺 The video in this post was made by freeCodeCamp.org
The origin of the article: https://www.youtube.com/watch?v=ua-CiDNNj30&list=PLWKjhJtqVAblfum5WiQblKPwIbqYXkDoC&index=7
🔺 DISCLAIMER: The article is for information sharing. The content of this video is solely the opinions of the speaker who is not a licensed financial advisor or registered investment advisor. Not investment advice or legal advice.
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For this week’s data science career interview, we got in touch with Dr Suman Sanyal, Associate Professor of Computer Science and Engineering at NIIT University. In this interview, Dr Sanyal shares his insights on how universities can contribute to this highly promising sector and what aspirants can do to build a successful data science career.
With industry-linkage, technology and research-driven seamless education, NIIT University has been recognised for addressing the growing demand for data science experts worldwide with its industry-ready courses. The university has recently introduced B.Tech in Data Science course, which aims to deploy data sets models to solve real-world problems. The programme provides industry-academic synergy for the students to establish careers in data science, artificial intelligence and machine learning.
“Students with skills that are aligned to new-age technology will be of huge value. The industry today wants young, ambitious students who have the know-how on how to get things done,” Sanyal said.
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The buzz around data science has sent many youngsters and professionals on an upskill/reskilling spree. Prof. Raghunathan Rengasamy, the acting head of Robert Bosch Centre for Data Science and AI, IIT Madras, believes data science knowledge will soon become a necessity.
IIT Madras has been one of India’s prestigious universities offering numerous courses in data science, machine learning, and artificial intelligence in partnership with many edtech startups. For this week’s data science career interview, Analytics India Magazine spoke to Prof. Rengasamy to understand his views on the data science education market.
With more than 15 years of experience, Prof. Rengasamy is currently heading RBCDSAI-IIT Madras and teaching at the department of chemical engineering. He has co-authored a series of review articles on condition monitoring and fault detection and diagnosis. He has also been the recipient of the Young Engineer Award for the year 2000 by the Indian National Academy of Engineering (INAE) for outstanding engineers under the age of 32.
Of late, Rengaswamy has been working on engineering applications of artificial intelligence and computational microfluidics. His research work has also led to the formation of a startup, SysEng LLC, in the US, funded through an NSF STTR grant.
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Data Science becomes an important part of today industry. It use for transforming business data into assets that help organizations improve revenue, seize business opportunities, improve customer experience, reduce costs, and more. Data science became the trending course to learn in the industries these days.
Its popularity has grown over the years, and companies have started implementing data science techniques to grow their business and increase customer satisfaction. In online Data science course you learn how Data Science deals with vast volumes of data using modern tools and techniques to find unseen patterns, derive meaningful information, and make business decisions.
Advantages of Data Science:- In today’s world, data is being generated at an alarming rate in all time lots of data is generated; from the users of social networking site, or from the calls that one makes, or the data which is being generated from different business. Because of that reason the huge amount of data the value of the field of Data Science has many advantages.
Some Of The Advantages Are Mentioned Below:-
Multiple Job Options :- Because of its high demand it provides large number of career opportunities in its various fields like Data Scientist, Data Analyst, Research Analyst, Business Analyst, Analytics Manager, Big Data Engineer, etc.
Business benefits: - By Data Science Online Course you learn how data science helps organizations knowing how and when their products sell well and that’s why the products are delivered always to the right place and right time. Faster and better decisions are taken by the organization to improve efficiency and earn higher profits.
Highly Paid jobs and career opportunities: - As Data Scientist continues working in that profile and the salaries of different position are grand. According to a Dice Salary Survey, the annual average salary of a Data Scientist $106,000 per year as we consider data.
Hiring Benefits:- If you have skills then don’t worry this comparatively easier to sort data and look for best of candidates for an organization. Big Data and data mining have made processing and selection of CVs, aptitude tests and games easier for the recruitment group.
Disadvantages of Data Science: - If there are pros then cons also so here we discuss both pros and cons which make you easy to choose Data Science Course without any doubts. Let’s check some of the disadvantages of Data Science:-
Data Privacy: - As we know Data is used to increase the productivity and the revenue of industry by making game-changing business decisions. But the information or the insights obtained from the data may be misused against any organization.
Cost:- The tools used for data science and analytics can cost tons to a corporation as a number of the tools are complex and need the people to undergo a knowledge Science training to use them. Also, it’s very difficult to pick the right tools consistent with the circumstances because their selection is predicated on the proper knowledge of the tools also as their accuracy in analyzing the info and extracting information.
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