Online Deep Learning Courses & Certifications

The PG level advanced certification programme in deep learning is offered by the Indian Institute of Science in collaboration with the talent spirit. The course provides knowledge about deep learning and how to apply it in the real world. The course provides practical knowledge about the development of machine learning algorithms and their use for hardware. Moreover, the course will cover the fundamentals of deep learning and its application.

The PG-level advanced certification programme in deep learning will be held in online mode with English as a medium of instruction. A visit to the Indian Institute of Science will be arranged for the students at the beginning or end of the course. The course duration will be 10 months. The course classes will happen only at weekends. The course will be instructed by the faculty of the Indian Institute of Science. Also, industry experts will share their experience and knowledge about the course application in the real world with the students. The fee structure of the course is Rs. 4,00,000 which has to be paid online. 

The PG Level Certification Course in Artificial Intelligence and Machine Learning by IIIT Hyderabad is a 9-month online course where three months are allotted for hands-on projects. This online certification course is designed for tech professionals equipping them with programming languages and tools. The PG Level Certification Course in Artificial Intelligence and Machine Learning online course from IIIT Hyderabad requires participants to complete this online certification course within 9 months. They can choose hands-on projects with advanced certification.

The PG Level Certification Course in Artificial Intelligence and Machine Learning syllabus covers various important topics taught by top faculty members. The course curriculum is specially designed for practitioners that will be delivered by live interactive lectures, mentored labs, projects and hackathons. Participants will also have opportunities to visit the campus and interact with an outstanding peer group. 

After completing the PG Level Certification Course in Artificial Intelligence and Machine Learning training from IIIT Hyderabad via TalentSprint, participants can work with global organizations like Accenture, Capgemini, Microsoft, MOBIS, Teradata, Deloitte and others. Get more details about the PG Level Certification Course in Artificial Intelligence and Machine Learning.

In the present times of rapid technological advancements and computerization, it has become extremely important to master the subject of Artificial Intelligence and Learning. This Post Graduate Certificate Program in Artificial Intelligence and Deep Learning has been planned for those candidates who want to master their skills in Machine Learning, Artificial Intelligence and Deep Learning. This blended/online program by Jigsaw Academy is in association with the Manipal Academy of Higher Education (MAHE).

The curriculum of this course has been designed in a way that will help the candidate to have hands-on practice of GPU Labs on real-world Case studies and 100+ hours of Cloud. It will develop an ability to plan and implement AI and DL for various business purposes. It will also focus on transforming the candidate into becoming an AI practitioner and applying machine learning and deep learning tools like Tensorflow, Keras and other algorithms.

The best thing about this program is that it will enrich the participant with detailed knowledge of the subject which will aid them in learning the different strategies to be applied. More than 10+ real-world scenarios will be presented wherein AI has been used across various industries and domains.

Deep learning falls under the broad spectrum of machine learning and can shadow the limitations and drawbacks that are evident in machine learning functions. We can say that deep learning is an ideal mechanism when the datasets are enormous. The Certified Deep Learning Expert Course can teach you how to apply deep learning knowledge to various organisational functions. 

Furthermore, the Certified Deep Learning Expert Course by DataMites includes case studies and real-world projects to impart relevant skills and maximum understanding. The programme curriculum comprises core learning algorithms, Tensorflow 2.X, neural networks, Recurrent neural network (Rnn), and more. 

Besides, DataMites offers different learning modes, including live virtual training, blended learning, and classroom training. You can opt for any option based on your preference and convenience.

DataMites’s Certified Deep Learning Expert certification course has been accredited by the International Association of Business Analytics (IABAC), and it carries worldwide recognition. You can benefit from the certification and fulfil your long-term career goals.

The Application of Deep Learning and Neural Networks Online Course is a digital course that discusses basic to advanced concepts of neural networks and deep learning. The course led by domain experts helps learners understand the practical applications of deep learning and artificial neural networks.

After completing the Application of Deep Learning and Neural Networks Certification by TCS iON, learners will get awarded a certificate of achievement. The course will be delivered through digital learning resources and digital lectures and evaluated through industry assignments, practice assessments and a final summative assessment.

The Certificate Course on Developing Deep Learning Applications is a self-paced 6 months course that is jointly developed, and also offered by the institutes' Intel Corporation, and ClouxLab. The candidates can start learning directly from the engineers of Intel, and the deep learning industry experts. With the syllabus of the course, one can learn how the developers can make use of the OpenVINO™ toolkit across industries

Certificate Course on Developing Deep Learning Applications training will be focused on developing different deep learning applications that can be used for demo stages, or learning stages of development of deep learning software. After the 2 certificates are offered the students will gain knowledge, and the expert skills for creating, and developing Computer Vision applications with the use of tools like Keras, OpenCV, Python, and Convolutional Neural Networks.

Post Graduate Certificate in Deep Learning for Computer Vision and Extended Reality training is an online programme offered jointly by Coursera and the Indian Institute of Technology Guwahati. The course will train the participants on the application of deep learning in extended reality (XR) and computer vision. The six-month-long online PG programme is designed for those who have a bachelor's degree. 

Post Graduate Certificate in Deep Learning for Computer Vision and Extended Reality by IIT Guwahati helps the learners advance their knowledge of machine learning and deep learning models. The programme consists of 6 courses on various aspects and 6 projects. The course provides comprehensive practical exposure through projects making the learning ready for the industry. 

Post Graduate Certificate in Deep Learning for Computer Vision and Extended Reality online course is tortured by the expert faculties from IIT Guwahati. Coursera also provides 2 weeks refund policy for this programme. 

Also, Read: Deep Learning Certification Courses

The Self-Driving Car Engineer programme is an exclusive Nanodegree course at Udacity, which encompasses all the key concepts and skills required to become a self-driving car engineer. This course houses numerous industry-relevant projects and renowned experts to help you learn invaluable skills and concepts such as computer vision, deep learning, localisation, controllers, sensor fusion, automotive hardware, vehicle kinematics, and more. 

The Self-Driving Car Engineer course by Udacity also provides you with the rare chance to run your code on Carla, Udacity’s very own autonomous vehicle, to see the real implementation of the skills you have learned. The course provides features such as a flexible learning module to suit your packed schedules, technical mentor support, personal career coaches, and experienced project reviewers to make your learning experience an efficient one.

Moreover, the Self-Driving Car Engineer training curriculum has been designed in partnership with tech and automotive giants such as BMW, DiDi, Uber ATG, NVIDIA, Mercedes, and McLaren. That gives the candidates an excellent opportunity to master the fundamentals while learning from the best in the industry.

The Certificate in Machine Learning and Deep Learning Batch I program by Education Lanes is one of the strongest certifications programs that keep student interest on the first hand, this is the thing that is given topmost importance always in this particular field. 

Machine learning and deep learning both have indeed been fields of research since the development of neural networking. Through technological advances, in particular the graphical processing units, the need for competent and trained staff in this field has been fulfilled. Applications of machine learning and deep learning vary from machine vision to voice recognition and interpretation to advertising and drug development. 

The Certificate in Machine Learning and Deep Learning Batch I certification course is structured in a prosperous way that includes thesis and research-based work modules with the single objectives of conducting a study on core machine learning and artificial intelligence technologies, which is language processing and improving learning along with some reinforcement aspects. 

This Certificate in Machine Learning and Deep Learning Batch I online course is designed with trying to develop quantitative mathematical skills using machine learning and deep learning methods and realistic execution of any technique for real-world implementations.

Today’s digital era has enabled the technologies to flourish exponentially. Computer systems are now able to derive more accurate results by analysing huge amounts of structured as well as unstructured data, commonly known now as ‘big data’. These advancements have assisted companies in reducing risks and identifying more profitable opportunities. The role of deep learning in this technology-driven era has assumed great significance. Deep Learning makes use of algorithms to enable automatic learning through absorption of information and data.

Being a specialized form of machine learning, deep learning enables end-to-end automatic learning using all the relevant features from the data provided. Many big brands and large organisations are extensively making use of deep learning to facilitate automation in their operations. This has led to a rise in demand for deep learning practitioners around the world.

The Deep Learning nanodegree programme course online offered by Udacity will enable you to master fundamentals of deep learning which will aid you in building a career in deep learning as well as pursue in-depth studies in the field of AI. The programme comprises 5 courses and 5 real-world projects to showcase your skills in the deep learning domain. This beginner-friendly nanodegree programme is the perfect way to get started in areas of machine learning and AI.

The Georgia Institute of Technology, USA, offers the Reinforcement Learning online programme by Udacity. This four-month-long course aims to teach you important Reinforcement Learning (RL) concepts. You will study through a blend of recent papers and classic work in the area.

Throughout the Reinforcement Learning online training, you will learn about automated decision-making from the point of view of Computer Science. The course offers in-depth learning content taught by industry professionals. You will learn via interactive quizzes, video lectures and practical exercises.

The Reinforcement Learning syllabus covers a wide range of RL topics comprehensively. These include convergence, generalisation, game theory, Bellman equations, MDP (Markov Decision Process), among others. You will also explore efficient algorithms, multiagent and single-agent planning, and more. 

The Reinforcement Learning course by Udacity also describes Temporal Difference (TD) learning and related concepts. You will also reiterate a result from a published paper in RL at the end of this advanced online programme.

Also Read:
Deep Reinforcement Learning Certification Courses

Deep Learning for Visual Computing course’s aim is to educate the student about the stratified recognition task. This is a free course that covers topics including visual computing, ResNet, PyTorch, Python, GoogleNet, and more.

Swayam Deep Learning for Visual Computing is an appropriate option for people who want to become deep learning scientists, get into research, computer vision engineer, AI research scientist, etc. Join this course to make a career as a software engineer, deep learning engineer, IT artificial intelligence intern, research scientist, computer scientist, etc. 

The course type is ongoing and the length for this course is 12 weeks. There are no strict fee charges to enrol or study the Deep Learning for Visual Computing course, but for the certificate, the student needs to register and appear in an examination conducted in person at a chosen center. Regular assessments and one-on-one doubt clearing sessions are held by IIT-affiliated teachers.

Over the past few years, Deep Learning has received a lot of attention due to its wide-ranging applications in data analytics, natural language processing, and computer vision. Many professionals who are well versed in deep learning technologies have been employed by leading companies like Google, IBM, Facebook, Microsoft, and Twitter. In this Deep learning – IIT Ropar online training, you will get familiar with the building blocks of deep learning algorithms and solutions.

The Deep Learning – IIT Ropar course syllabus places a particular emphasis on neural network topics like attention mechanisms, convolutional neural networks, feed-forward neural networks, and recurrent neural networks. Various deep learning optimisation algorithms such as Nesterov Accelerated Gradient Descent, Gradient descent, Adam, AdaGrad, and RMSProp are also covered. Learning these algorithms and methods will help effectively train deep neural networks.

After completing all the lectures and assignments of the Deep Learning – IIT Ropar programme, you’ll have a robust grasp of deep learning architectures, which you can employ to carry out various computer vision and Natural Language Processing tasks. You can also test your understanding by applying for the final proctored exam. Passing this test will also grant you a certificate by Swayam, which can be used to display your skills and get lucrative jobs.

The availability of massive amounts of image and video data on the internet has made data interpretation and analysis a challenging affair. However, deep learning has proved to be an excellent solution to such a mammoth task. Moreover, deep learning is not only applicable to data analysis but also computer vision and natural language processing tasks. This Deep Learning - IITKGP course will help you get familiar with the concept and its applications.

The Deep Learning - IITKGP course syllabus starts with traditional machine learning methods like multilayer perceptron and Bayesian classification. Towards the end, the course will discuss modern deep learning approaches like autoencoders and convolutional neural networks. After completion, you will have the knowledge and confidence to take on challenging, real-world problems related to data analysis and automation.

By opting for the Deep Learning - IITKGP certification course, you also get industry support from Adobe, TCS, Google, and DRDO. Moreover, the course’s scheduled nature also provides you with enough motivation to study the modules and complete the course. After every module, you can find challenging assignments, which help you gauge your understanding.

The Deep Learning for Computer Vision certification course offers a comprehensive curriculum that covers the core aspects of deep learning for computer vision. The duration of this certification course is 12 weeks and completion of a basic course in Machine Learning course, and basic knowledge in probability, linear algebra, calculus, and Python are the prerequisites for this course.  

The students will explore the traditional computer vision topics before they learn about the deep learning methods for computer vision. The Deep Learning for Computer Vision certification by NPTEL provides the basics as well as the latest advancement skills and knowledge in the field of computer vision and machine learning.

Also Read: Online Machine Learning Courses & Certifications

Deep learning is a powerful technology that is being used to solve problems in many different areas. Deep Learning is a 10-week-long online certification course which is brought to you by Carnegie Mellon University’s School of Computer Science Executive and Professional Education along with the online education provider Emeritus. This online course will teach you the basics of deep learning and how to apply it to real-world problems. With the help of this course, you will be able to understand how neural networks operate, identify the right architecture for your needs, and generate and refine deep learning models.

The Deep Learning certification by Carnegie Mellon University’s School of Computer Science will teach you the basics of deep learning and how to apply it to real-world problems. You will learn about different neural network architectures, including CNNs and RNNs. You will also learn about the concepts necessary to solve time-based problems.

Also Read: Online Deep Learning with Python Certification Courses

There is no doubt that the AI revolution is being driven by deep learning. Machine learning and AI are gaining popularity as it helps make data-driven business decisions. With a deep understanding of AI & ML, you can take your business to an all-new level.  PyTorch makes it convenient to build applications used for deep learning. The programme will teach you how to build and train deep neural networks using Pytorch. This practical experience would hone your skills to use them in your personal projects. 

Intro to Deep Learning with PyTorch online course explores how to use PyTorch using coding exercises and projects. This will help you implement state-of-the-art AI applications such as text generation and style transfer.  This is a free course that offers instructional videos, interactive quizzes, and self-paced learning. 

Intro to Deep Learning with PyTorch takes about two weeks to complete. This is an intermediate-level course and requires a working knowledge of Python and its libraries Matplotlib and NumPy. The industry experts for this course are a panel of five educators: Matt Leonard, Soumith Chintala, Luis Serrano, Cezanne Camacho, and Alexis Cook. 

Introduction to TensorFlow Lite Certification teaches how to deploy (DL) deep learning models on mobile and embedded devices with TensorFlow Lite. It includes various programming languages support such as Java, Swift, Objective-C, C++, and Python.

Introduction to TensorFlow Lite Classes is developed by the TensorFlow team and Udacity together as a practical approach to model deployment for software developers. All candidates get hands-on experience with the TensorFlow Lite framework as you deploy deep learning models on Android, iOS, and even an embedded Linux platform. 

By the end of this Introduction to TensorFlow Lite Training, all candidates will have the skills necessary to start deploying their own deep learning models into mobile apps.

Introduction to TensorFlow Lite Certification Course is designed for aspirants who want to learn TensorFlow Lite to execute efficiently on most devices with limited compute and memory resources. All students after completion of classes get Introduction to TensorFlow Lite Certification by Udacity.

The Fuzzy Logic and Neural Networks certification is a multidisciplinary course which can be pursued by graduate or postgraduate students. Students who decide to pursue this course will get to know about fuzzy clustering, fuzzy reasoning, neural network, etc. The programme does not have any limitations regarding the admission process and can be joined by the interested students throughout the year without having to pay any amount. The course is provided as well as mentored by the Indian Institute of Technology, Kharagpur. The teachings of the course are in online mode throughout the Fuzzy Logic and Neural Networks certification syllabus of the course.

The Fuzzy Logic and Neural Networks programme is conducted by the platform of Swayam which is a government-initiated platform and gives free courses to all the students across the country. The duration which is needed to complete the course is 2 months. Candidates can learn from the programme as per their schedules since this is a self-paced course. The online training authorizes the students to be a certified user of the programme by obtaining the certificate through the mode of an exam fee followed by the offline exam. The Fuzzy Logic and Neural Networks online course also provides interactive sessions through case studies and discussions which can be done through the discussion groups created for the user of the course.

Deep learning, also known as deep neural learning or deep neural network, is an artificial intelligence functionality that resembles the functioning of the human brain in digesting data and developing correlations used in decision making. Deep Learning and Computer Vision online certification is designed by Board Infinity, an online educational platform for job applicants and learners that will assist them in realizing their full potential to achieve their career goals. 

Deep Learning and Computer Vision online course focuses on providing a hands-on experience of the core concepts and principles associated with deep learning and computer vision. Deep Learning and Computer Vision online classes include approximately 25 hours of live lectures on a variety of data science topics, including natural language processing and neural networks, such as convolutional and recurrent neural networks. Candidates will have developed competencies in technologies such as OpenCV, Jupyter, Tensorflow, Python, Numpy, and others by the end of this course.

The Deep Learning - Part 2 certification course covers a comprehensive curriculum that includes an intersection of Deep Learning and Generative Modeling, Restricted Boltzmann Machines, Markov Chains and Gibbs Sampling for training RBMs. The students gain hands-on training from expert professionals in the industry. This course provides from basic to in-depth discussion on the subject.    

The Deep Learning - Part 2 certification by NPTEL course duration is 8 weeks and deep learning is the prerequisite for this course. This course benefits the students to equipped with the necessary skills and knowledge to excel in the deep learning field. The course can be obtained by BE/BTech/ME/MTech/MS/PhD students.

Also Read: Online Deep Learning Courses & Certifications

The intermediate-level Customizing Your Models with TensorFlow 2 online course by Coursera builds a strong knowledge base for TensorFlow. You will learn to develop customized deep-learning models and workflows for any application. Additionally, the certification course will teach you how to build complex model architecture using lower-level APIs in TensorFlow.

Towards the course end, you will be working on a Capstone Project to apply the concepts you acquired over the course duration. You will custom-build a neutral translation model from scratch. The Customising Your Models with TensorFlow 2 programme, is the second course of the three-part Specialization – TensorFlow 2 for Deep Learning Specialisation. Moreover, the world-renowned institute, Imperial College of London, offers the online course, while Dr Kevin Webster instructs it.

You will learn via pre-recorded lectures and development experience, along with the coding assignments, which offer practical and field-relevant practice. A graduate teaching assistant will guide you through the projects. Most importantly, the Customising Your Models with TensorFlow 2 online course is entirely self-paced with flexible deadlines to suit your comfort.

The Deep Learning in Computer Vision online course by Coursera is focused on introducing learners to computer vision, right from the basics. Eventually, the certification course moves to deep learning models which are more modern. Image, as well as video recognition, is a primary part of the programme. The comprehensive curriculum will cover image annotation and classification, motion estimation, human action recognition, and more.

Moreover, Deep Learning in Computer Vision programme is the fifth course in the Advanced Machine Learning Specialization. The National Research University Higher School of Economics offers an online course in association with Coursera. The Deep Learning in Computer Vision certification course is an advanced-level course with a self-paced learning option. You will also work on a final project to implement their learnings. 

In the course project for the Deep Learning in Computer Vision course, you will learn to build face recognition and manipulation systems. This project will help you get an idea about the internal mechanics of this technology. The online course also includes a shareable certificate which you will receive from Coursera upon successful completion. 

This course is tailor-made for students who are already coding in Python. This course is more advanced and tends to coders or developers who are interested in Deep Learning. Deep Learning is a little different from Machine Learning and deals with Artificial Intelligence. Deep learning is an AI functionality which tries to recreate human behavior when it processes data for purposes of detection of objects and speech, language translation and decision-making.

With this course, the student will be able to successfully differentiate between Deep Learning and Machine Learning. After the student learns the basic concepts of Deep Learning, they will learn how to successfully navigate the TensorFlow 2.x package in this course. A deeper dive will be taken when learning about the above concepts and topics such as CNN, RCNN, LSTM, RNN and RBM will be introduced.

After finishing the course, the students will be able solve real-time projects using these concepts. The projects could include emotion and gender detection or auto image captioning and many others.

The Deep Learning Essentials program by edX will help candidates discover the issues of discrimination and bias in Machine Learning and gain valuable insights regarding the subject. They will become adept at performing tasks like signal processing, computer vision, robotics, sequential decision-making, and natural language processing.

Besides, the University of Montreal offers the Deep Learning Essentials training which is designed by IVADO, a hub of scientific and economic data science and Mila. The scientific director of this course is Yoshua Bengio, a reputed expert in artificial intelligence and a pioneer in Deep Learning, who is also a professor at the University of Montreal.

Rife with video tutorials, tests, and assignments, the Deep Learning Essentials certification course also provides diverse learning tools to help candidates become adept in deep learning's fundamental concepts and methods. 

On successful course completion, candidates can also secure a verified certificate from edX to acknowledge their newly acquired knowledge in the field. The candidates may choose from any one of the tracks available namely verified and audit to complete the programme. Both the tracks are self-paced but during the audit track, the candidates shall receive limited period access to the course. On the other hand, the verified track will offer unlimited time for accessing the course.

The Applied Deep Learning Capstone Project certification programme is a five-week-long online course curated by IBM. During this capstone project, you will get practical, hands-on experience in developing, training and testing a Deep Learning model. For this purpose, you will be using either PyTorch or Keras.

edX’s Applied Deep Learning Capstone Project is an advanced-level programme that is also a part of a Deep Learning professional certificate of edX. With the help of this course, you will learn how to preprocess and load data for a real-life problem, create a model and finally validate it. 

The Applied Deep Learning Capstone Project programme by edX requires only two to four hours per week to study. You will learn through video lessons and ultimately master the procedure of generating a Deep Learning pipeline. At last, you are required to present a project report to showcase your competence in the domain of Deep Learning. EdX provides two tracks to pursue the self-paced course; verified and free audit. In the former mode, the learners can access the programme unlimited and get a certificate of completion. In the free mode, they can audit it for a limited duration. 

Training sophisticated Deep Learning models takes plenty of time. The Using GPUs to Scale and Speed-up Deep Learning certification programme sheds light on how accelerated hardware like Nvidia GPU (Graphics Processing Unit) or Google’s TPU (Tensor Processing Unit) can be used to shorten computations time on the cloud.

During edX’s Using GPUs to Scale and Speed-up Deep Learning course, you will understand what accelerated GPU-based hardware is and how it can help you overcome scalability challenges in Deep Learning. You will also get familiar with IBM’s Power Systems with Power AI and Nvidia GPU.

The Using GPUs to Scale and Speed-up Deep Learning will also acquaint you with popular Machine Learning dependencies and learnings supported by Power AI. These include Caffe, Theano, Tensorflow and Torch. Lastly, with this course, you will get practical experience of deploying Deep Learning networks on accelerated hardware for numerous problems, such as classifying videos and images.

The Deep Learning Fundamentals with Keras online course by edX is designed to familiarise you with the domain of Deep Learning. It is a five-week-long programme, during which you will learn about the basics of various Deep Learning models, the fundamentals of neural networks, and some of the most interesting Deep Learning applications.

Through the Deep Learning Fundamentals with Keras certification course, you will get practical experience, building a Deep Learning model with the powerful and easy-to-use Keras library. Also, you will develop an understanding of unsupervised and supervised Deep Learning models.

The Deep Learning Fundamentals with Keras certification syllabus is divided into four extensive modules. You are required to devote merely two to four hours every week to your studies.  As you progress across the modules, you acquire in-depth knowledge of how Keras is used to train, test and build Deep Learning models. Moreover, you will understand how neural networks learn. Upon completion, you can also get the verified certificate and earn a skill badge to showcase your acquired knowledge if you pursue it by paying free. For free, you can get a limited duration of access to the course. 

Understanding deeply the technique of Deep learning in teaching which guarantees skills and knowledge for lifelong learning by using a range of contemporary digital technologies to enhance the learning, forms the main aim for the intermediate course on Deep learning through transformative pedagogy. This certification course is provided by edX, an online education provider in association with University of Queensland and Microsoft, both known for its educational and technological contributions and the course is taken by the professors from the institution. 

This self-paced Deep learning through transformative pedagogy online course with no required prerequisites comprises a curriculum which is specially curated for educators and education leaders but can be opted by anyone with a keen interest in learning and exploring the technique of deep learning.

The education & teacher training course mainly focuses on exploring deep learning and how it makes the students become more connective, collaborative and creative problem tacklers. Different powerful learning activities and teaching strategies are studied in order to facilitate deep learning which makes your students become innovative creators, effective communicators, and independent thinkers.