Online Top 5 Artificial Intelligence Courses, Certifications and Classes
Are you interested in learning Artificial Intelligence skills? These AI courses, certificates, and training programs will assist you in gaining skills and preparing you for a bright career in artificial intelligence and machine learning.
Artificial intelligence is now being used in a wide range of businesses. The possibilities are unlimited in the fields of healthcare, banking, mobile, vehicle, smart thermostats, music, and movies. A person can experience retail, security monitoring, fraud detection, virtual player games, and social networking apps.
Almost every company is attempting to incorporate artificial intelligence (AI) into its operations and products. Anyone who learns AI may therefore open up a world of possibilities. A mix of AI, machine learning, and deep learning can pave the road to a bright future in the workplace.
With a range of programs and training available online, learning Artificial Intelligence (albeit not simple) has become much more accessible. These are taught by the top AI educators, researchers, and specialists, and are frequently far less expensive than a traditional college course.
Some of these seminars are highly extensive and cover the material that would be covered in a college degree. Some of them are even free, and they’re great for getting a taste of the AI world.
To assist you in making the best decision, we’ve prepared a list of the finest Great Learning artificial intelligence online courses, workshops, credentials, training programs, and tutorials accessible online that you can utilize to get a solid foundation in the area.
1. Stanford University’s Machine Learning
The popularity of this artificial intelligence certificate course may be gauged by the fact that it has already been taken by 3.5 million students and professionals, with 93 percent of them giving it a 5-star rating. Without question, AI specialists recommend this course as probably the most important resource for anybody interested in learning AI and machine learning.
Learners will be introduced to the fundamental concepts of machine learning, data mining, and statistical pattern identification in this course. It gives students a solid foundation in the mathematical, statistical, and computer science basics that automated learning machines are built on. With about 55 hours of information spread out over 11 weeks, the course material is rather substantial.
The course includes several case studies and applications to allow students to obtain hands-on experience. They will use learning algorithms to create smart robots (perception, control), text comprehension (web search, anti-spam), machine vision, healthcare analytics, audio, information mining, and other fields.
2. Specialization in Deep Learning
Deep Learning is an area of AI that is rapidly evolving and is responsible for many of AI’s breakthroughs and revolutions. This is a much more advanced training course for those who want to learn more about Machine learning and artificial intelligence, but also how to apply it to problems and pursue a career in AI.
Students should be comfortable with Programming skills and arithmetic, as well as have some understanding and experience with machine learning, as this is not a beginning course.
In addition, courses address a variety of real-world case studies in fields like medical, autonomously driving, gesture recognition reading, music production, and natural language processing. Students work on a variety of intriguing projects, including developing a facial recognition system and a rudimentary translation system, among others.
There are also interviews and conversations with top executives and pioneers in the industry, which provide students with professional guidance, and motivation and help them understand the challenges they will encounter in the real world.
Important Points to Remember
- Familiarize yourself with AI and deep learning theory, as well as how they are used in the industry.
- Exercise Python and TensorFlow skills
- Know how to construct deep learning apps using industry best practices.
- Seek input from deep learning professionals and thought leaders.
- Be able to use TensorFlow to build a neural network
- Understand how to create and train Back Propagation Neural networks (RNNs), as well as commonly-used versions such as GRUs and LSTMs, and how to detect problems in a predictive model and prioritize strategies for minimizing error.
3. Reinforcement Learning in Python (Artificial Intelligence Course)
In AI and Machine Learning, Reinforcement Learning is a whole distinct paradigm. It has given us incredible insights into behavioral psychology and neurology, and it is the nearest approximation we have to a truly general artificial intelligence that we have so far.
This is one of the greatest AI Reinforcement Learning courses available. It provides an overview of AI-powered reinforcement learning, with an emphasis on stock trading and online advertising. It reveals AI approaches that are not found in typical supervised methods, uncontrolled machine learning, or deep learning.
This session is best suited for people who already have a basic understanding of the concepts and technical components of AI and want to learn more about Supervised Learning. Algebra, Statistics, Device programming, Python coding, Numpy coding, Regression models, Gradient descent, and other advanced ideas are required of students.
4.TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning: An Introduction
TensorFlow is a well-known open-source machine learning framework that is perhaps the greatest tool for implementing machine learning and deep learning algorithms and concepts.
This course is for software engineers who want to design scaled AI-powered algorithms in TensorFlow and have some expertise with Python coding and some expertise in machine learning and deep learning. It demonstrates how to utilize TensorFlow to implement machine learning and data mining concepts, allowing students to begin creating and deploying scalable models to real-world situations.
5. Business Applications of Artificial Intelligence and Machine Learning
The Great Learning’s PG in ai and machine learning teaches you the most extensively used tools and procedures in the business, and it is based on both theory and practice. The University of Texas at Austin is teaming up with Great Learning to provide the artificial intelligence online course to students all around the world.
Great Lakes and UT Austin-McCombs built the PGP-Artificial Intelligence and Machine Learning curriculum, including learning content and tests provided by Great Lakes, UT Austin, IIT-Bombay, and other practicing data scientists and Artificial Intelligence professionals. Upon completion, all successful participants get dual certification from Great Lakes and The University of Texas at Austin.
The Bottom Line
The artificial intelligence generated by machines is the ability of a computer to execute activities that were previously considered to need human intellect. Gameplay, translation software, expert systems, and robotics are all examples of typical uses.
Although pseudo-intelligent machines have existed since antiquity, the introduction of digital computers in the 1940s brought the first glimpses of actual intelligence. AI, or at least the appearance of intelligence, has progressed in lockstep with computational processing capacity, which appears to be the primary bottleneck.
In comparison to visual pattern recognition, complicated decision-making, and natural language, early AI initiatives like playing chess and solving mathematical problems are considered basic today.