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Artificial Intelligence is the big thing in the world of technology. From self-driving cars to automated robots to NPCs in our games to simple things like AI processing of images in our smartphones, Artificial Intelligence is now entrenched in our daily lives. And if you are looking to have a long future as a developer and get the highest paying jobs, you need to have the required skills to work in the AI field. Thankfully, there are tons of online courses that can not only get you started on AI but also help you become a professional AI developer. To make your life easier, we have listed the 10 best Artificial Intelligence courses online that can help you in your learning journey.

In this article, we have mentioned beginners, intermediate, and advanced Artificial Intelligence courses. So no matter where you are in your Artificial Intelligence learning journey, you will find a course on AI that will help you improve your skills. With that said, lets dive into our best AI learning courses list, shall we?

This course on Artificial Intelligence will teach you to combine the power of Data Science, Machine Learning, and Deep Learning to create powerful AI for real-world applications. This is a big course with 16.5 hours of video lectures, 17 articles, and 1 downloadable resource. Once you complete this course you will also get a Certificate of Completion which you can use in your next job hunting endeavor. Before you start this course, you should know that it requires you to have a basic knowledge of High School Mathematics and the Python language. If you dont know Python, there are several courses on Python that can get you started.

What I love about this course is that it focuses on teaching you real-world application of AI. Going through this course you will build an AI, create a virtual self-driving car, understand the theory behind AI, make an AI to beat games, and more. Also, since this course is on Udemy, you can buy it once and have lifetime access for it. Theres no subscription pricing involved so it is quite light on your wallet. If you are thinking of starting the AI journey, this is the course you should check out. After all, it is one of the best if not the best Artificial Intelligence courses online.

Course Rating: 4.4 (Rated by 11,783 students)

Difficulty level: Beginner to Advanced (requires basic knowledge of Python and high school mathematics)

Buy Course on Udemy: Starting at $13.99

Another great course to help you kick-start your AI learning journey is the Artificial Intelligence Masterclass on Udemy. In this course, you will learn to develop a powerful Artificial intelligence model based on a robust Hybrid Intelligence System. The course cover topics on fully-connected neural networks, recurrent neural networks, AutoEncoders and Variational AutoEncoders, evolution strategies, and more. To help you learn all these concepts, you get 12 hours of step-by-step video guide and the full roadmap which will help you build your own Hybrid AI Model from scratch.

The course also provides a toolkit and that you can use to build hybrid intelligent systems. You also get a Certificate of Completion which comes handy when hunting for a job. The course is great but before you take it you should know its basic requirements. You need to have a working knowledge of high school mathematics and previous coding experience. You dont need to be an expert coder to start this course but this is also not meant for someone who is just starting to code. If you want to build hybrid intelligent systems, then this is one of the best online Artificial Intelligence courses that you can find right now.

Course Rating: 4.5 (Rated by 478 students)

Difficulty level: Intermediate to Advanced (requires basic knowledge of coding and high school mathematics)

Buy Course on Udemy: Starting at $13.99

One of the biggest applications of AI is in games. From generating random maps and levels to creating interactive NPCs (Non-Playable Characters / Non-Player Characters), AI handles a large portion of our games today. If the gaming industry is where you want to apply your Artificial Intelligence skills then this is the course for you. The main purpose of this course is to provide you with a practical guide to program non-player characters for games. The course focuses on developing NPCs in the Unity engine which is a popular gaming engine used for developing games across multiple operating systems.

In this course, you will learn to design and code NPCs in C#. The course will give you a detailed explanation on the use of AI in games and teach you to implement AI-related Unity Asset plugins into existing projects. Finally, you will also learn to work with a variety of AI techniques for developing navigation and decision making abilities in NPCs. The course has 9 hours of video content with 12 articles and 62 downloadable materials. Like other Udemy courses, you can buy it once for lifetime access and will receive a Certificate of Completion after you are done with the course.

Course Rating: 4.2 (Rated by 1242 students)

Difficulty level: Intermediate to Advanced (Requires familiarity with C# and the Unity Game Development Engine)

Buy Course on Udemy: Starting at $13.99

Stanford University is one of the top-most universities in the world and was ranked third in Times Higher Education ranking of universities across the globe. If thats not enough, you should know that this course is taught by Andrew Ng who was the founder of Googles deep learning research unit, Google Brain, Head of AI at Baidu, and is currently the CEO/Founder of Landing AI. The course on AI and ML that we are featuring is available completely online that means you dont have to be physically present at the university to take classes. That also means that it is way cheaper than attending school. The course covers AI and ML from the basics to advanced level so you can get started with your Artificial Intelligence journey. It provides a broad introduction to machine learning, data mining, and statistical pattern recognition.

Its a vast course with 56 hours of content that is spaced over 10 weeks. It starts with basic topics such as Linear Algebra, Linear Regression with Multiple Variables, Logistic Regression, and more and then move onto advanced lectures on Neural Networks, application of Machine Learning, Unsupervised Machine Learning, and more. Not only that, you also get graded assignments and quizzes that will help you go through this course and solve your doubts. Finally, you will also get an electronic certificate of completion from Stanford University which has its value. This is one of the best developed online courses on Artificial Intelligence and you should not ignore it.

Course Rating: 4.9 (Rated by more than 118,348 students)

Difficulty level: Advanced

Subscribe on Coursera: $49/month (financial aid available)

If you want to take a university course like the one featured above but cannot afford to pay for it then you should take this Machine Learning course provide by the Artificial Intelligence faculty of Columbia University. The course is available on edX which provides university-level courses for free. You only have to pay if you want the certificate from University. If you just want to learn then the course is free which is great for users who dont have that kind of cash. Talking about the course, it focuses on AI and ML models and methods and teaches you to 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.

The course takes 12 weeks to complete with 8-10 hours of work required every week. The topics include classification and regression, clustering methods, sequential models, matrix factorization, topic modeling and model selection, and more. The course focuses on both supervised and unsupervised learning techniques so you develop an all-around knowledge or Artificial Intelligence and Machine Learning. Its one of the best courses on Artificial Intelligence online right now.

Course Rating: No course ratings available at edX

Difficulty level: Advanced

Enroll on edX: Free, $375 for Electronic Certificate from Columbia University

Another good course on Artificial Intelligence comes from IBM, a company that has been at the forefront of AI innovation. After you have completed this course you will have a complete understating of Machine Learning and Deep Learning and you will be able to apply them in your professional projects. The course covers the fundamental concepts of Machine Learning and Deep Learning, including supervised and unsupervised learning. You will learn to use multiple ML and DL libraries such as SciPy, ScikitLearn, Keras, PyTorch, and Tensorflow and apply them to solve problems involving object recognition and Computer Vision, image and video processing, text analytics, and more.

One of my favorite things about this course is that it not only teaches you but also makes you apply the knowledge through a system of hands-on projects. You can use these projects to both build your skills and develop your portfolio which will help you during job hunting. You will also earn a certificate that will be recognized by various professional hiring partners that can help you land good jobs. If you want to work in the AI industry this is one of the best Artificial Intelligence courses online that you can take.

Course Rating: No Ratings Available

Difficulty level: Advanced

Subscribe on Coursera: $49/month (financial aid available)

One of the lesser-known applications of Artificial Intelligence is in the field of business where it is used to optimize workflow and processes to enhance business operations and solve real-world problems. If that is what you are interested in then this is the online Artificial Intelligence course for you. Available on Udemy, the course comes with 15 hours of on-demand video lectures, 16 articles, and 1 downloadable resource to help you learn AI for Business. Once you buy it, you can access life allowing you to learn the course at your pace.

Talking about the course structure it starts with the basics of business optimization AI by teaching you how to build an optimization model powered by AI. Then you will learn to use Artificial Intelligence to improve various business processes such as maximizing efficiency, minimizing costs, maximizing revenue, implementing Deep-Q learning, and more. In the process, you will understand how to build an artificial brain and master the general AI framework. This is a great course on AI for anyone who is looking to introduce AI enhancements in their business.

Course Rating: 4.6 (Rated by 1,145 students)

Difficulty level: Beginner (requires basic knowledge of Python and high school mathematics)

Buy Course on Udemy: Starting at $11.39

Microsoft is one of the leading companies that is pushing AI forward. Its doing that by not only using and evolving AI in multiple fronts of its business but also by providing a complete course on AI which anyone can take to start their AI journey. This is a vast course that requires 2-4 months and in total 224-356 hours of effort. It is so vast because its not a single course but consists of 11 courses all of which combine will take you from AI novice to a professional AI developer.

The course starts by introducing you to Python for Data Sciences and then move onto topics such as Deep Learning, Natural Language Processing, Reinforcement Learning, Computer Vision and Image Analysis, Principles of Machine Learning and more. I love that theres even a section on ethics of AI which is something many courses forget to include. After completion of the course, you will receive a certification course from Microsoft which you can use when applying for AI jobs. Overall, I find this to be one of the most complete online course on Artificial Intelligence.

Course Rating: No course ratings available at edX

Difficulty level: Advanced

Enroll on edX: Free (limited access) $980.10

This course provides a complete guide to Artificial Intelligence and prepares you for Deep Reinforcement Learning with Stock Trading Applications. This is an advanced course and requires prior knowledge of Calculus, Probability, Markov Models, Gradient descent, Python, and more subjects. If you are a beginner do not buy this course. With that out of the way, lets take a look at what this course has to offer, shall we?

Well, the course is quite short with only 9.5 half hours of video lectures. However, while the run-time is short, unpacking everything in the classes will take you a ton of time. In this course, you will learn to apply gradient-based supervised machine learning methods to reinforcement learning, understand reinforcement learning on a technical level, and implement 17 different reinforcement learning algorithms. if you want to get into reinforcement learning of AI, this is the course for you.

Course Rating: 4.6 (Rated by 5,528 students)

Difficulty level: Advanced

Buy Course on Udemy: Starting at $11.39

Another premier institute that is offering its Artificial Intelligence online course is MIT. Its AI Implications for Business Strategy course focuses on organizational and managerial implications of these technologies, rather than on their technical aspects. That means its not meant for developers rather for managers who want to pioneer the successful integration of AI in business. It is a 6-week online program (6-8 hours of work every week) that presents you with a foundational understanding of where we are today with AI and how we got here.

The course focuses on three prime AI technologies which include Machine Learning, Natural Language Processing, and Robotics. As I mentioned before the program is meant for managers and high-level executives and aims to help them effectively analyze, articulate, and apply key AI management and leadership insights in their work. So, if you find yourself in a position of instituting AI in your business this is the course you should take. The only drawback of this course is that its quite costly at $3,200. If you can afford to buy it, you should check it out.

Course Rating: 4.8

Difficulty level: Beginner to Advanced

Enroll on MIT Website: $3200

That ends our article on the best online courses on Artificial Intelligence. While I have tried my best to make this as beginner-friendly as possible, you will require a basic knowledge of coding (preferably Python) if you want to get started with AI. Artificial Intelligence is already dominating the core technology and its importance is only going to increase over time. So, check out these courses and select one to start your AI learning journey.

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10 Best Artificial Intelligence Courses Online in 2020 ...

DUBLIN--(BUSINESS WIRE)--The "Geospatial Analytics Artificial Intelligence Market - Forecast (2020 - 2025)" report has been added to ResearchAndMarkets.com's offering.

The global geospatial analytics AI market is estimated to grow at a CAGR of 24.00% during the forecast period 2020-2025.

APAC is projected to be the fastest-growing market with a CAGR of 32.6%, which can be mainly attributed to the growing usage of geospatial analytics across various booming industrial sectors as well as the growing infrastructural developments in the region.

Geospatial Analytics AI Market Outlook

Geospatial Analytics Artificial Intelligence employs Artificial Intelligence technologies such as deep learning and machine learning to combine geographic information system (GIS) with business intelligence information. Geospatial Analytics AI finds a wide range of applications in logistics, transportation, surveying, agriculture, sales and marketing, medical and others. The multidisciplinary applications of Geospatial Analytics AI is primarily due to the assistance of the technology in decision making, resource planning and allocation that are essential in many industries. According to Industry ARC findings, the hazard assessment application segment will hold the largest market share during the forecast period.

Geospatial Analytics AI Market Growth Drivers

The growth of the transportation industry is expected to drive the geospatial analytics AI market during the forecast period. The aviation industry is a major segment where technology can be helpful in streamlining operations by controlling air traffic and increasing safety and security in airports. The growing fraudulent activities in the Banking, Financial Services, and Insurance (BFSI) sector are also expected to drive the market for Geospatial Analytics AI Market.

Geospatial Analytics AI Market Challenges

High costs of technology is a major challenge that is hampering the adoption of technology despite a wide number of applications across various industry verticals. Additionally, there are many national laws and regulations imposed by various countries that curtail the growth of the industry.

Geospatial Analytics AI Market Research Scope

The base year of the study is 2020, with forecast done up to 2025. The study presents a thorough analysis of the competitive landscape, taking into account the market shares of the leading companies. It also provides information on unit shipments. These provide the key market participants with the necessary business intelligence and help them understand the future of the Geospatial Analytics AI Market. The assessment includes the forecast, an overview of the competitive structure, the market shares of the competitors, as well as the market trends, market demands, market drivers, market challenges, and product analysis. The market drivers and restraints have been assessed to fathom their impact over the forecast period. This report further identifies the key opportunities for growth while also detailing the key challenges and possible threats.

Geospatial Analytics AI Market Report: Industry Coverage

Key Topics Covered:

1. Geospatial Analytics Artificial Intelligence Market - Overview

2. Geospatial Analytics Artificial Intelligence Market - Executive summary

3. Geospatial Analytics Artificial Intelligence Market

3.1. Comparative analysis

3.1.1. Product Benchmarking - Top 10 companies

3.1.2. Top 5 Financials Analysis

3.1.3. Market Value split by Top 10 companies

3.1.4. Patent Analysis - Top 10 companies

3.1.5. Pricing Analysis

4. Geospatial Analytics Artificial Intelligence Market Forces

4.1. Drivers

4.2. Constraints

4.3. Challenges

4.4. Porters five force model

5. Geospatial Analytics Artificial Intelligence Market -Strategic analysis

5.1. Value chain analysis

5.2. Opportunities analysis

5.3. Product life cycle

5.4. Suppliers and distributors Market Share

6. Geospatial Analytics Artificial Intelligence Market - By Data Source (Market Size -$Million / $Billion)

6.1. Market Size and Market Share Analysis

6.2. Application Revenue and Trend Research

6.3. Product Segment Analysis

7. Geospatial Analytics Artificial Intelligence Market - By Solution (Market Size -$Million / $Billion)

7.1. Hardware

7.1.1. Memory

7.1.2. Processor

7.1.3. Others

7.2. Software

7.2.1. By Deployment

7.2.1.1. Cloud

7.2.1.2. On-Premise

7.3. Services

8. Geospatial Analytics Artificial Intelligence Market - By Machine Learning (Market Size -$Million / $Billion)

8.1. Unsupervised Learning

8.2. Supervised Learning

8.3. Reinforced Learning

8.4. Semi-supervised Learning

8.5. Deep Learning

8.6. Others

9. Geospatial Analytics Artificial Intelligence Market - By Applications (Market Size -$Million / $Billion)

9.1. Geographic Information

9.2. Real Estate

9.3. Coastal application

9.4. Sales & Marketing

9.5. Fraud Detection

9.6. Transport & Logistics

9.7. Agriculture

9.8. Surveying

9.9. Hazard assessment

9.10. Natural Resource Management

9.9. Others

10. Geospatial Analytics Artificial Intelligence - By Geography (Market Size -$Million / $Billion)

10.1. Geospatial Analytics Artificial Intelligence Market - North America Segment Research

10.2. North America Market Research (Million / $Billion)

10.3. Geospatial Analytics Artificial Intelligence - South America Segment Research

10.4. South America Market Research (Market Size -$Million / $Billion)

10.5. Geospatial Analytics Artificial Intelligence - Europe Segment Research

10.6. Europe Market Research (Market Size -$Million / $Billion)

10.7. Geospatial Analytics Artificial Intelligence - APAC Segment Research

10.8. APAC Market Research (Market Size -$Million / $Billion)

11. Geospatial Analytics Artificial Intelligence Market - Entropy

11.1. New product launches

11.2. M&A's, collaborations, JVs and partnerships

12. Geospatial Analytics Artificial Intelligence Market - Industry / Segment Competition landscape Premium

12.1. Market Share Analysis

12.1.1. Market Share by Country- Top companies

12.1.2. Market Share by Region- Top 10 companies

12.1.3. Market Share by type of Application - Top 10 companies

12.1.4. Market Share by type of Product / Product category- Top 10 companies

12.1.5. Market Share at global level- Top 10 companies

12.1.6. Best Practises for companies

13. Geospatial Analytics Artificial Intelligence Market Company Analysis

13.1. Market Share, Company Revenue, Products, M&A, Developments

13.2. Google

13.3. Microsoft

13.4. Geoblink

13.5. ESRI

13.6. Trimble Inc.

13.7. HEXAGON

13.8. Harris Corporation

13.9. Digital Globe

13.10. Bentley Systems

13.11. Incorporated

13.12. General Electric

14. Geospatial Analytics Artificial Intelligence Market - Appendix

For more information about this report visit https://www.researchandmarkets.com/r/isah13

See more here:
Geospatial Analytics Artificial Intelligence Market (2020 to 2025) - Drivers, Constraints and Challenges - ResearchAndMarkets.com - Business Wire

Were halfway through 2020 and its safe to say that the year will be forever associated with the COVID-19 pandemic. For most of the last six months travel restrictions, lockdowns, social distancing and mask wearing have been put in place in an attempt to curtail the spread. Now, as the world attempts to reopen, governments and businesses must deal with the dual problems of restarting after the shutdowns and, in the absence of a vaccine, trying to contain further outbreaks. Technology is playing a key role in the research trying to understand the virus and eventually developing that vaccine. Can it also play a part in containing the spread until it is deployed? Can it help life return to normal?

Addfor, an Italian company with almost two decades of experience in Artificial Intelligence Solutions development for engineering, has created an AI-enabled system called citySAFE that can help to monitor so-called hot spots as well as mitigation efforts in an attempt to limit the spread. citySAFE interfaces with already installed camera systems or mobile cams, to provide aggregate information for either outdoor or indoor public and private spaces. Lenovo is collaborating with Addfor by defining and providing the right system hardware configuration to support the immense raw processing power required by a high camera-count video streaming.

The citySAFE application relies on a simplified interface that displays critical situations in real-time, leveraging available data about infection and hospitalization rates, then color-coding areas accordingly. For example, if a hot spot springs up, citySAFE can, in real time, assess the extent to which mitigation efforts in that area are being followed. All indices, such as counting populations, population density, or percentage of mask usage are calculated in real-time and grouped in space and time to be explored both geographically and temporally with an advanced graphical interface. Health officials can then issue warnings and deploy personnel to remind people and businesses about masks social distancing, and other safe practices. This same scenario could play out for a private company with a large footprint campus, manufacturing or distribution complex.

citySAFE was recently tested on a large scale in Turin, Italy with the collaboration of the public administration and other local authorities. It is the only integrated system available at the moment that allows the timely and continuous monitoring of an entire city, either from city surveillance or aerial cameras, for the issues related to the control of the spread of the COVID-19 virus. By using existing city camera infrastructure, citizens are subjected only to their existing level of CCTV observation.

This type of continuous streaming of live video data requires tremendous processing power, both at the edge, where the video is captured, and in the data center where the results are compiled, run through the algorithms for inference, distributed and retrained. In this context, Lenovo is providing the unique rugged ThinkSystem SE350 edge server. By using the computational power of the high-performance NVIDIA T4 GPU, the ThinkSystem SE350 delivers video streaming wirelessly from cameras, and real-time inference at the edge. On the back end, the Lenovo GPU dense ThinkSystem SR670, designed to support up to eight high-performance NVIDIA V100 GPUs, is built for running large AI workloads such as citySAFE and scales linearly as requirements grow. Both the ThinkSystem SE350 and SR670 are built on Intel Xeon processors for optimal performance and security.

We know that the pandemic will not go on forever: A vaccine will be found and deployed. Life will return to normal. When it does, citySAFE and its associated infrastructure can be repurposed for developing new or enhancing existing services the city administration or private companies provide citizens or employees such in areas such as safety, parking management, waiting times, and advanced digital signage systems for traffic or missing persons alerts.

In 2100s, future historians will study the COVID-19 pandemic, the same way that weve studied the Spanish Flu outbreak of 1918. They will see the mistakes from 1918, some corrected, some repeated, in 2020. And they will see a global crisis fought on a local basis. Mitigating the spread of the virus in the interim until a vaccine is developed, while restarting the economies of the world, is the tightrope we find ourselves on now. How we execute those precarious steps may end up being the yardstick by which those future historians measure us. In the face of these challenges, how did we get life to return to normal?

Go here to see the original:
Using Artificial Intelligence in the Fight Against COVID-19 - HPCwire

Artificial intelligence once relegated to academic studies and sci-fi nerds has become one of the hottest technologies, infiltrating every industry.

AI adoption was already accelerating before the COVID-19 crisis, but experts say that demand for AI tools is now is poised to grow even faster.

"The entire industry of AI is getting a huge boost from this unfortunate crisis," David Blumberg, founder and managing partner at Blumberg Capital, told Business Insider in May. "There is a silver lining to this dark cloud that we've all been living in for over two and a half, three months."

Former Cisco CEO John Chambers, who now runs his own venture firm JC2 Ventures, told Business Insider in an interview in May that he expects one to five major AI players to emerge from the current crisis.

AI has helped businesses take on big and small tasks, from making long-term sales growth projections to the automation of routine, time-consuming tasks.A 2019 Gartner survey found that major organizations planned to double their number of AI-related initiatives in the following year, from an average of 4 to 10. But as they pandemic has forced businesses to try to adapt to major changes, like the sudden pivot to remote work and tightening budgets, they're looking for ways to streamline and operate more efficiently.

"AI is best at solving all these really boring meat-and-potato problems," James Cham, a partner at Bloomberg Partners, told Business Insider. Many of the opportunities for using AI involve "straightforward process engineering," he said, where the technology can be used to shorten or streamline a process.

Industries like collaboration, shipping logistics, and manufacturing and warehousing will be particularly keen on using AI, said Sandeep Bhadra, a partner at Vertex Ventures.

Jake Saper at Emergence Capital had a similar prediction, that "vertical" specific AI software will be in more demand.

Here are 12 startups that analysts and investors say are well-positioned to grow thanks to a surge in demand for AI tools:

Originally posted here:
These 12 artificial intelligence startups are poised for success, particularly in a post-COVID world, according to experts - Business Insider

Researchers have figured out a way to transform a few dozen pixels into a high resolution image of a face using artificial intelligence.

A team from Duke University in the US created an algorithm capable of "imagining" realistic-looking faces from blurry, unrecognisable pictures of people, with eight-times more effectiveness than previous methods.

"Never have super-resolution images been created at this resolution before with this much detail," said Duke computer scientist Cynthia Rudin, who led the research.

Sharing the full story, not just the headlines

The images generated by the AI do not resemble real people, instead they are faces that look plausibly real. It therefore cannot be used to identify people from low resolution images captured by security cameras.

The PULSE (Photo Upsampling via Latent Space Exploration) system developed by Dr Rudin and her team creates images with 64-times the resolution than the original blurred picture.

The PULSE algorithm is able to achieve such high levels of resolution by reverse engineering the image from high resolution images that look similar to the low resolution image when down scaled.

The images generated by enhancing the pixels do not represent real people (Duke University)

Through this process, facial features like eyelashes, teeth and wrinkles that were impossible to see in the low resolution image become recognisable and detailed.

"Instead of starting with the low resolution image and slowly adding detail, PULSE traverses the high resolution natural image manifold, searching for images that downscale to the original low resolution image," states a paper detailing the research.

The AI algorithm is able to enhance a few dozen pixels into a high-resolution picture of a face (Duke University)

"Our method outperforms state-of-the-art methods in perceptual quality at higher resolutions and scale factors than previously possible."

The system could theoretically be used on low resolution images of almost anything, ranging from medicine and microscopy, to astronomy and satellite imagery.

This means noisy, poor-quality images of distant planets and solar systems could be imagined in high resolution.

The research will be presented at the 2020 Conference on Computer Vision and Pattern Recognition (CVPR) this week.

Continued here:
Artificial intelligence enhances blurry faces into 'super-resolution images' - The Independent