In the changing tech scenario in India, noted and well-established institutes have now also started to step forward and train students as well as the professionals in artificial intelligence and machine learning. The institutes are providing both the current needs of algorithms and mathematical insights as well as practical experiences. In this article, we list 5 tier-1 institutes that have added courses on artificial intelligence in India. About The Programme: This institute launched a dual degree specialisation in data science as well as in robotics in the year 2018. Any B.Tech student can enroll in this programme based on the CGPA cut-off of 8.0 at the end of the 5th semester.
Artificial Intelligence is still pretty much in its nascent stage, but one thing that we've all noticed through its limited period of implementation is that the technology is here to stay. Not only is AI making lives easier for all of us living in this world, but it is also creating a doorway towards the future, as we had envisioned it to be. While AI promises to deliver a lot of goods in the future, there is still the presence of the human element involved. The human element is required for the means of maintaining big data numbers, solving AI problems, teaching machines how to learn and store data, among many other aspects. Now, while machines need humans for the proper functioning of Artificial Intelligence, individuals working alongside these machines should boast of a special skill set developed through years of experience.
This is one of the most comprehensive course on any e-learning platform (including Udemy marketplace) which uses the power of Python to learn exploratory data analysis and machine learning algorithms. You will learn the skills to dive deep into the data and present solid conclusions for decision making.
H2O is the world's number one machine learning platform. It is an open-source software, and the H2O-3 GitHub repository is available for anyone to start hacking. This hands-on guide aims to explain the basic principles behind H2O and get you as a data scientist started as quickly as possible in the most simple way. The rest is just machine learning. After reading this guide, you'll be able to: As a data scientist, you're most likely to use R and/or Python. Interestingly, H2O makes it easy to seamlessly switch Python, R, and other data science tools while still working on the same project. This allows data scientists to interact more easily, as well as use the best tool for the job, but the possibilities do not stop there. H2O also offers its own web-based interface named Flow. By means of Flow, data scientists are able to import, explore, and modify datasets, play with models, verify models performances, and much more. Flow is beautiful and a quick way to do machine learning.
The Information Technology world is waiting for you. This wonderfully flexible, object-oriented language is best learnt when it is learnt with examples. Simpliv offers tons of examples to help you understand the concepts and learn how to implement them in real life to integrate systems. Our course offers you knowledge of how to put Python to the highest use it is capable of being put to: web development, GUI, software development, system admin, and what not. Ideal for anyone who wants to put Python to its optimal use.. Programmers, Developers, Technical Leads, Architects, Freshers,Data Scientists, Data Analysts,Business Intelligence Managers.
Learn to carry out pre-processing, visualization and machine learning tasks such as: clustering, classification and regression in R. You will be able to mine insights from text data and Twitter to give yourself & your company a competitive edge. I use easy-to-understand, hands-on methods to simplify and address even the most difficult concepts in R. My course will help you implement the methods using real data obtained from different sources. Many courses use made-up data that does not empower students to implement R based data science in real life. After taking this course, you'll easily use packages like caret, dplyr to work with real data in R.
This course is the right resource for anyone with some knowledge of Java programming who wants to get started with Data Science and Machine learning as quickly as possible. If you want to gain meaningful insights from big data and develop intelligent applications using Java, this course is also a must-have. Machine Learning is one of the core area of Artificial Intelligence where computers are trained to self-learn, grow, change, and develop on their own without being explicitly programmed. This course demonstrates complex data extraction and statistical analysis techniques supported by Java, applying various machine learning methods, exploring machine learning sub-domains, and exploring real-world use cases such as recommendation systems, fraud detection, natural language processing, and more, using Java programming. The course begins with an introduction to data science and basic data science tasks such as data collection, data cleaning, data analysis, and data visualization.
Data is the new oil. And Machine Learning is the fire. Whoever controls these two will control the world. No, the above is not some pompous phrase picked up from a dystopian novel. The new world order is all about collecting vast amounts of relevant data and processing it into actionable insights -- something the human race hasn't been able to do in history.
Big data analytics and machine learning are on the rise and set for massive further growth over the coming years. The results of a survey conducted jointly by MIT Technology Review and Google Cloud showed that 60 percent of respondents have already implemented a machine learning strategy in their organization. Furthermore, Deloitte predicts that spending on machine learning (ML) and AI will nearly quadruple from $12 billion in 2017 to $57.6 billion in 2021. Amidst this growing popularity, a growing concern is that algorithms are only as good as the data that's fed into them. The old adage "garbage in, garbage out" applies to AI and ML as much as it does to any other computing-based system.