Top Free Online Courses

 Want To Learn From Global Educators:Here Are Some Top Free Courses

Want to learn something that could make you separate from the mob.
I have some solutions to this problem.!

Due to the COVID-19 pandemic the rate of unemployment rate in India has rose to 7.78% and globally the unemployment rate is probably 13%.The technology is taking quantum leaps of development.The learning pattern is changing now a days.The online method of teaching is the perfect example of advancement of technology.The top institutes or the premier institutes are teaching their various courses through online platforms.

"Online learning is rapidly becoming one of the most cost-effective ways to educate the world's rapidly expanding workforce.” - Zig Ziglar 

In today's era your  value is estimated  by the skill you have learned not the degress that you had pursued.The benefits of these online courses are very vast.The learnings would help you in your nearby future but here are some benefits of pursuing these online courses.

1.Reduced Costs
Online education can cost less due to a variety of reasons. For example, there is no cost for commuting. Assorted costs that are related to transport, such as fuel, parking, car maintenance, and public transportation costs don't affect the online student.


2.Flexibility

Students have the freedom to juggle their careers and school because they aren't tied down to a fixed schedule. In a traditional classroom setting, class meeting times are set, and the student has no power over this, forcing them to work their schedules around these dates.

3. Access to Expertise
An online college education might give students access to specialized degree courses that may not be available in an easily accessible or local institution of learning. For example, at CCA you can pursue a degree in Marketing or a certificate in C++ Programming without having to live near the institution. Online classes allow the sharing of expertise that helps more people have access to education that is not readily available in certain geographic locations.


4.You can learn whatever you want!

You can pick the program of your dreams in traditional education, too, but that would involve traveling away from home, living in a completely unknown city, and struggling in an extremely competitive learning environment. With online education, you can take any program or course present in traditional four-year universities.

5.Online courses look great on a resume and makes good impression

It doesn’t matter where your career stands at this moment; an online program will always look good on your resume. It will show potential employers that you’re committed to learning and you’re eager to obtain more knowledge and new skills. Hiring managers don’t see online degrees as inferior to traditional ones. A degree is a degree. If you obtain an online degree from a prestigious university, you’ll boost your career with the speed of light. You will certainly become a better candidate for a job promotion, and your resume will look much better when you apply for new positions.

Digital Duo has made a collection of all these course which you can explore below in the field of computer science.


1.CS50's Introduction to ComputerScience from Harvard University 

This is CS50x, Harvard University's introduction to the intellectual enterprises of computer science and the art of programming for majors and non-majors alike, with or without prior programming experience. An entry-level course taught by David J. Malan, CS50x teaches students how to think algorithmically and solve problems efficiently. Topics include abstraction, algorithms, data structures, encapsulation, resource management, security, software engineering, and web development. Languages include C, Python, SQL, and JavaScript plus CSS and HTML. Problem sets inspired by real-world domains of biology, cryptography, finance, forensics, and gaming. The on-campus version of CS50x, CS50, is Harvard's largest course.


2.Algorithms, Part I  from Princeton University 

This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations. Part I covers elementary data structures, sorting, and searching algorithms. Part II focuses on graph- and string-processing algorithms.
All the features of this course are available for free. 


3.Algorithms, Part II from Princeton University 

This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations. Part I covers elementary data structures, sorting, and searching algorithms. Part II focuses on graph- and string-processing algorithms.


4.Machine Learning: Unsupervised Learning from Brown University 

This is the second course in the 3-course Machine Learning Series and is offered at Georgia Tech as CS7641. Taking this class here does not earn Georgia Tech credit.

Ever wonder how Netflix can predict what movies you'll like? Or how Amazon knows what you want to buy before you do? The answer can be found in Unsupervised Learning!

Closely related to pattern recognition, Unsupervised Learning is about analyzing data and looking for patterns. It is an extremely powerful tool for identifying structure in data. This course focuses on how you can use Unsupervised Learning approaches -- including randomized optimization, clustering, and feature selection and transformation -- to find structure in unlabeled data.

5.Robotics: Perception from University of Pennsylvania 

 In this module, we will study how images and videos acquired by cameras mounted on robots are transformed into representations like features and optical flow. Such 2D representations allow us then to extract 3D information about where the camera is and in which direction the robot moves. You will come to understand how grasping objects is facilitated by the computation of 3D posing of objects and navigation can be accomplished by visual odometry and landmark-based localization.

6.Analysis of Algorithms from Princeton University 

This course teaches a calculus that enables precise quantitative predictions of large combinatorial structures. In addition, this course covers generating functions and real asymptotics and then introduces the symbolic method in the context of applications in the analysis of algorithms and basic structures such as permutations, trees, strings, words, and mappings.


7.Enabling Technologies for Data Science and Analytics: The Internetof Things from Columbia University 

In this data science course, you will learn about the major components of the Internet of Things and how data is acquired from sensors. You will also examine ways of analyzing event data, sentiment analysis, facial recognition software and how data generated from devices can be used to make decisions.



8.Computer Architecture from Princeton University 

In this course, you will learn to design the computer architecture of complex modern microprocessors.All the features of this course are available for free



9.Software Defined Networking from Princeton University 

In this course, you will learn about software defined networking and how it is changing the way communications networks are managed, maintained, and secured.


10.Machine Learning from Georgia Institute of Technology 

Machine Learning is a graduate-level course covering the area of Artificial Intelligence concerned with computer programs that modify and improve their performance through experiences.

The first part of the course covers Supervised Learning, a machine learning task that makes it possible for your phone to recognize your voice, your email to filter spam, and for computers to learn a bunch of other cool stuff.

In part two, you will learn about Unsupervised Learning. Ever wonder how Netflix can predict what movies you'll like? Or how Amazon knows what you want to buy before you do? Such answers can be found in this section!

Finally, can we program machines to learn like humans? This Reinforcement Learning section will teach you the algorithms for designing self-learning agents like us

11.Reinforcement Learning from Brown University 

You should take this course if you have an interest in machine learning and the desire to engage with it from a theoretical perspective. Through a combination of classic papers and more recent work, you will explore automated decision-making from a computer-science perspective. You will examine efficient algorithms, where they exist, for single-agent and multi-agent planning as well as approaches to learning near-optimal decisions from experience. At the end of the course, you will replicate a result from a published paper in reinforcement learning.



12.Artificial Intelligence (AI) from Columbia University 

What do self-driving cars, face recognition, web search, industrial robots, missile guidance, and tumor detection have in common?

They are all complex real world problems being solved with applications of intelligence (AI).

This course will provide a broad understanding of the basic techniques for building intelligent computer systems and an understanding of how AI is applied to problems.

You will learn about the history of AI, intelligent agents, state-space problem representations, uninformed and heuristic search, game playing, logical agents, and constraint satisfaction problems.

Hands on experience will be gained by building a basic search agent. Adversarial search will be explored through the creation of a game and an introduction to machine learning includes work on linear regression.

13.Machine Learning from Columbia University

Machine Learning is the basis for the most exciting careers in data analysis today. You’ll learn the models and methods and apply them to real world situations ranging from identifying trending news topics, to building recommendation engines, ranking sports teams and plotting the path of movie zombies.

Major perspectives covered include:

• probabilistic versus non-probabilistic modeling
• supervised versus unsupervised learning

Topics include: classification and regression, clustering methods, sequential models, matrix factorization, topic modeling and model selection.

14.Machine Learning for Data Science and Analytics from Columbia University 

Machine Learning is a growing field that is used when searching the web, placing ads, credit scoring, stock trading and for many other applications.

This data science course is an introduction to machine learning and algorithms. You will develop a basic understanding of the principles of machine learning and derive practical solutions using predictive analytics. We will also examine why algorithms play an essential role in Big Data analysis.

15.Bitcoin and Cryptocurrency Technologies from Princeton University 

After this course, you’ll know everything you need to be able to separate fact from fiction when reading claims about Bitcoin and other cryptocurrencies. You’ll have the conceptual foundations you need to engineer secure software that interacts with the Bitcoin network. And you’ll be able to integrate ideas from Bitcoin in your own projects.

Online Education Is Totally Worth The Effort!

Online courses and degree programs are more convenient and cheaper than their counterparts in traditional education. Those are the two main advantages of online learning that lead many students to opt for online platforms when they want to earn a degree or certificate.
The best thing about online learning is that you can learn in a relaxed manner even if you don’t want to get certified. You only need passion for learning and a quick online search that will take you to the right course. From that point on, you will be the master of your own education.

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