on 09 August 23
By now almost every tech company has realised that the world needs more artificial intelligence and machine learning experts. There are only 10,000 people in the world right now with the education, experience and talent needed to develop these AI technologies. This acute lack of skill set is hindering digital transformation at enterprises across the globe.
To meet this talent shortage, the tech giants have now become more committed to making ML more accessible to students and developers by offering online courses.
AI can solve complex problems and has the potential to transform entire industries, which means it’s crucial that AI reflect a diverse range of human perspectives and needs, Zuri Kemp, technical program manager at Google, said.
Let’s take a look at a few important ML courses offered by some of the noted tech companies:
Career Progression/Transition into Artificial Intelligence and Machine Learning?
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1. Learn with Google AI (Google)
Google has been pursuing AI education for a while and now, as they want to educate more people in AI and ML with a free online course. Early this year, Google launched a new website called Learn with Google AI. This website is meant to be an information hub for anyone who wants to learn about core Machine Learning concepts, develop and hone their ML skills, and apply ML to real-world problems. The new website aims to cater everyone starting from students to curious cats, and advanced researchers. The California-based tech giant has repeatedly stated its goal to democratise AI and make its tools available for everyone.
2. ML Crash Course (Google)
The Learn with Google AI website also features a free course called ML crash course (MLCC) with TensorFlow APIs. Google originally designed this course for its employees as a part of a two-day boot camp aimed to give a practical introduction to ML fundamentals. More than 18,000 employees have already enrolled in MLCC, enhanced camera calibration for Daydream devices, built VR for Google Earth, and improved streaming quality at YouTube. Now, Google is making MLCC available to everyone.The 15 hours online course includes real-world case studies, interactive visualisation, video lectures, over 40 exercise to help teach ML concepts.
3. Microsoft Professional Program For AI (Microsoft)
Microsoft is focused on empowering both people and organisations, by democratising access to AI to help solve most of their pressing challenges. Earlier this month, the tech company launched a new course on its tech accreditation scheme, called, Microsoft Professional Program, which is dedicated to AI. This course is aimed at developers who are looking to expand their AI capabilities as well as anyone interested in general AI education. The program consists of 10 courses that cover maths, statistics, Python, data analysis, computer vision, ethics, Azure ML, speech recognition and NLP. Each course takes between eight and 16 hours to complete.
However, these courses are not free. The students need to buy certificates from edX.org for each course. Once you complete the course you will receive a digitally-sharable Microsoft Professional Program Certificate in AI.
4. Introduction to ML (Amazon)
Last year, Amazon launched two new courses to educate developers and leverage AI solutions using Amazon Web Services:
This is a free 40-minute web-based training intended for developers, solution architects and IT decision makers who know about the foundations of working with AWS. It gives an overview of ML, walks through a use case, teaches relevant terminology, and walks the user through the process for incorporating ML solutions into a business or a product.
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5. Deep Learning on AWS (Amazon)
This is a one-day instructor-led training for developers who are interested in learning more about AWS solutions for deep learning. It teaches the deep learning model and gives the users a roadmap for understanding the challenges deep learning can solve. It also covers solutions related to image recognition, speech recognition, and speech translation. The training includes how to run your models on the cloud using an Amazon Elastic Compute Cloud (Amazon EC2)-based Deep Learning Amazon Machine Image (AMI) and the MXNet framework.
6. Deep Learning Course (NVIDIA)
The Deep Learning Institute by Nvidia comprises of both the hands-on training session and online course for AI enthusiasts. The topics of the course revolve around becoming a self-driving car engineer, creating smarter robots using deep learning with tools like Microsoft Azure, predicting the risk of disease, preventing it and more. It also includes instructor-led seminars, workshops, classes that reach developers across Asia, Europe and US.
The hands-on training is taught by certified experts from Nvidia partnering companies and universities, wherein they cover fundamentals of deep learning with topics like AI for object detection and image classification with TensorFlow, neural network deployment with DIGITS, and inference optimisation for an autonomous vehicle with TensorRT. The online classes are delivered through AWS and Google’s Qwiklabs.
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7. Deeplearning.ai (Baidu)
Baidu’s Deeplearning.ai offers training to coders who don’t have a background in AI or know much about deep learning. Here, the only thing required to pursue this course is basic programming knowledge, a proficiency in Python and a general understanding of ML. The course was launched by Andrew Ng, a former chief scientist at Baidu in 2017. It aims to spread the benefit of recent advances in ML far beyond big tech companies. The course cost $49 a month and is offered via Coursera. It features five tracks that include neural networks, backpropagation, convolutional nets and recurrent nets. It also teaches other core aspects of deep learning. The students also get to participate in applied deep learning projects to address real-world problems in language understand, healthcare and music generation.
8. Intel Student Ambassador Program for AI (Intel)
The Intel Student Ambassador Program for AI is the developer affinity program for university students to engage with Intel around their work in ML, deep learning and AI. The tech company is working with universities across the world to introduce this program. The students who are invited as Student Ambassadors are provided with technical support, resources and marketing to advance their work through Intel software, tools and hardware, said the company. The program is targeted toward graduate, undergraduate and PhD students.
9. Uber AI Residency (Uber)
This is a one-year research training program offered by Uber AI Labs and Uber ATG Toronto, to allow researchers accelerate their careers in ML and AI research and practice. The students will have the opportunity to work directly with researchers and engineers from across the company. The students also get to publish their work externally at top ML venues.
Career Advice From Machine Learning & Data Science Experts
There is no one size fits all solution. Your situation could be different (educational background, experience etc.), this is where experts and mentors from Machine Learning & Data Science field understand your profile better and guide you in the right path.
Here are some of the experts who are willing to help you achieve your career goals. They conduct a personal one–to–one over Skype and discuss your profile and areas for improvement.
- Arihant Jain (Specialist: Machine Learning, Data Science, Predictive Modelling)
- Jose Munoz Mata (Specialist: Data Science, AI, Career Development)
- Ujjyaini Mitra (Specialist: Data Science, Career movement to Data science)
- Mario Lewis (Specialist: Data Science, Big Data and Analytics)
- Sabrish Surender (Specialist: Data Science, Big Data, IoT, Cloud)
- Harpreet Dua (Specialist: Data Science, Business Analytics)
- Ganapathy Govindan (Specialist: Data Science, Big Data)
- Tarun Sukhani (Specialist: Data Science)
To sum up, these courses offered by the tech giants are not only trying to plug the talent gap but are also bringing more developers and students onboard to develop AI. Such initiatives will also break down barriers for AI teams to share their best practises and research to maximise social benefits and tackle ethical concerns and make it easier for students from other fields to get more access to ML. Eric Boyd, corporate vice president at Microsoft AI and Research rightly recapitulated, ML has the ability to transform the way we work, interact and communicate. To make this happen we need to put the right tools in the right hands.
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