Deep Learning technology has recently surfaced as a hot trending domain under Machine Learning. Its rapidly growing popularity is mainly due to the vast untapped potential for real-world applications. Although now we have many advanced Deep Learning applications like autonomous cars, recommendation engines, and smart virtual assistants, we’re witnessing only the tip of the iceberg.
What is Deep Learning?
Deep Learning is an advanced branch of Machine Learning designed to imitate the biological brain’s processing pattern to create meaningful insights for data-driven decision making. Deep learning technology leverages the power of artificial neural networks (ANNs) to mimic the biological brain’s data processing ability.
Neural nets can learn from unstructured and unlabeled data with minimal or no human supervision. An ANN comprises multiple layers arranged in a hierarchical structure. When information passes the first layer in the hierarchy, it transforms the data into a little more complex data and passes it to the next level. This process continues until the data reaches the last layer to deliver the desired output.
Deep Learning technology is used for object detection, speech recognition, machine translation, facial recognition, disease detection systems, and much more. Today, Deep Learning is used by retail, manufacturing, healthcare, agriculture, hospitality, cybersecurity, and energy industries, to name a few.
As the industry application for Deep Learning expands and diversifies, so will the demand for skilled and qualified Deep Learning experts. If you aspire to build a career in Data Science, acquiring Deep Learning skills can be a real turning point in your career. The best way to start your Deep Learning journey is to enroll in Deep Learning courses.
Keep reading until the end to find out the best Deep Learning courses worth your time and money!
Best Deep Learning Courses
Here’s a list of the best online Deep Learning courses offered by the best in the game:
Google has been actively involved in its pursuit of Artificial Intelligence, Machine Learning, and Deep Learning technologies. Google has always actively contributed to growing the Data Science community, right from developing innovative products to delivering relevant courses on these emerging technologies.
Google offers a whole range of AI/ML learning resources and programs for Data Science aspirants. In essence, Learn with Google AI is an information hub for anyone who wants to learn about core ML and Deep Learning concepts and sharpen their real-world technology skills.
This free online ML course was initially designed for Google employees as part of a 2-day boot camp. The 15-hour course focuses on introducing learners to fundamental concepts of ML. It includes 25+ lessons, over 30 exercises, interactive visualizations, and real-world case studies to help you understand Machine Learning and Deep Learning better.
This training program teaches you how to leverage the latest developments in ML and AI to foster innovation. You get to explore and work with Google Cloud tools like BigQuery, Cloud Speech API, Datalab, and TensorFlow. Also, you learn how to integrate these tools with Machine Learning APIs like Cloud Vision.
Apart from this, the course includes other relevant modules like ML on Google Cloud, Automate Interactions with Contact Center AI, and Explore ML models with Explainable AI.
Surprisingly, LinkedIn has a vast pool of learning resources on AI, ML, and Deep Learning. These courses can range anywhere from 10 minutes to 16 hours, offering in-depth knowledge on specific topics and helping Data Science enthusiasts to gain niche skills.
This is the first part of LinkedIn’s Applied ML course divided into five modules – introduction, ML basics, exploratory data analysis & data cleaning, measuring success, optimizing a model, and end-to-end pipeline.
Besides gaining in-depth knowledge of ML, students learn about the difference between AI, ML, and Deep Learning technologies. Thus, the course covers ML’s essential bases, right from the core concepts to using the right ML tools and algorithms for creating a pipeline for ML model development.
In this LinkedIn course, you’ll learn all about ML and Deep Learning concepts, tools, and their applications, all in 17 hours! The course consists of nine modules: Building Deep Learning applications with Keras 2.0, Deep Learning:
Like Google, Microsoft is heavily invested in Artificial Intelligence and Machine Learning. It seeks to empower organizations, professionals, and students by democratizing AI knowledge by offering a host of interactive courses on AI, ML, and Deep Learning.
Microsoft has partnered with NASSCOM FutureSkills® to create and deliver a one-of-a-kind learning experience – AI Classroom series. The classroom series includes three modules covering the basics of AI, Machine Learning, and Deep Learning. It aims to train Data Science aspirants to master their domain knowledge via easy-to-consume modules, simulative demos, and practical assignments and workshops.
Students will develop a deep understanding of different cognitive tools and how to use them to build intelligent solutions on course completion.
This Microsoft course focuses on AI and is designed for Data science professionals looking to extend their AI knowledge and abilities. Students interested in entering the AI field can also take this course.
It includes ten courses covering essentials like maths, statistics, data analysis, computer vision, Python, Azure ML, speech recognition, Deep Learning, and NLP. The courses require anywhere between 8 to 16 hours of learning.
After the launch of Amazon Web Services, the eCommerce giant launched two courses on ML and Deep Learning to educate Data Science enthusiasts and experts and teach them how to harness the potential of Amazon Web Services.
This free Amazon course is best suited for IT developers, architects, and decision-makers who are aware of AWS’s basics. In 40 minutes, the course offers a detailed overview of Machine Learning, explains all relevant terminologies, elaborates on a use case, and teaches how to integrate AI and ML solutions into business strategies or product development processes.
This Amazon course is a one-day program designed for candidates interested in gaining in-depth knowledge of AWS’s workings. It is an instructor-led training course that teaches you how to leverage AWS solutions for Deep Learning. Thus, you will learn how to run Deep Learning models on the cloud using Amazon EC2-based Deep Learning, Amazon Machine Image (AMI), and the MXNet framework. Plus, you also learn about image recognition, speech recognition, and speech translation.
Also Read: Short Term Job Oriented Courses
upGrad strives to be the pioneer of online learning in India by delivering cutting-edge courses on the most trending topics in the industry, including Data Science, Machine Learning, Artificial Intelligence, Blockchain, and so much more.
This 6-month course is designed for working professionals. Covering over 240+ hours of learning, this course includes five modules – Data Science Tool Kit, Statistics and Exploratory Data Analytics, Machine Learning, Machine Learning II, and Deep Learning. Besides teaching theoretical concepts, learners also work on different industry projects, case studies, and assignments. On course completion, students get placement assistance.
In this 6-month course, you’ll not only learn all the fundamentals of Machine Learning and Natural Language Processing, but you’ll also work with tools like Python, Pandas, Numpy, NLTK, MySQL, and Excel. The program includes more than five industry projects and case studies. Students get dedicated mentorship and placement assistance from expert instructors of IIIT-Bangalore.
This upGrad course is delivered in collaboration with IIT-Madras and Liverpool John Moores University. In 18 months, the program will cover areas like Big Data processing using Spark, deploy ML models, supervised & unsupervised ML, and predictive analytics.
The tool suite comprises Python, TensorFlow, MySQL, Hadoop, Hive, Spark, and AWS. Students work on over 25 case studies, assignments, workshops, and a four-week industry Capstone Project.
If you are looking to upskill for a career transition or are simply interested in gaining Data Science knowledge and skills, these are the courses you should consider!
We hope this helps!