Online Deep Learning Courses & Certifications

By taking up the Specialized Models: Time Series and Survival Analysis online course the students will be working on the ways to identify the modelling challenges that are common within the domain of time series data. The course will further be helping to understand the process of how trends are gauged and accessed in a time series of data. In the Specialized Models: Time Series and Survival Analysis certification syllabus the students will be covering chapters on- Identifying Nonstationarity, Common Transformations, Smoothing Moving Averages, Time Series Smoothing, Deep Learning Notebook, Survival Analysis and Censoring and others. The online course on Specialized Models: Time Series and Survival Analysis by Coursera will be elaborating on the domains of “time-series data” and will be working on its applications.

The AI Capstone Project with Deep Learning certification course provides an advanced level of training to all its participants. The programme is within the reach of the students at no cost as it can be accessed for free in the audit mode. The course is made accessible to every aspirant through the platform Coursera. Students who enrol for this hundred per cent online training will be able to gain a deep understanding of AI. 

The course revolves around the topics of preprocessing data, building a model, validity of a model, etc. The programme is a part of a course named IBM AI Engineering that is also a Coursera programme and is in association with IBM. The curriculum of the AI Capstone Project with Deep Learning online course is managed by two industry experts that will help the students understand the concepts. 

The course material of the subject also provides hands-on experience through projects. Along with the projects, it includes quizzes, assignments, practises exercises, etc. The course does not have any restrictions with respect to admission eligibility criteria, deadlines, or attendance. The content of the AI Capstone Project with the Deep Learning certification syllabus is divided into 4 weeks and can be completely finished in around 16 hours. If the student is able to complete the course in the fixed time he or she will be able to achieve a certificate at the end of the programme.

Fundamentals of Deep Learning certification course is created by Board Infinity, a learning system that aims to help individuals achieve excellence and achieve their professional goals. The Fundamentals of Deep Learning online classes by Board Infinity are for students who are looking for a thorough training program that will help them develop a solid understanding of the principles and practices of deep learning.

Fundamentals of Deep Learning online course is a self-paced learning program that includes more than 6 hours of detailed video lectures, as well as numerous projects, case studies, and assignments to give students a well-rounded learning experience. This course starts with a basic introduction to machine learning and then moves on to more advanced subjects like neural networks. Students will have a thorough grasp of how to use Python, Pandas, NumPy, Tensorflow, and Anaconda for a variety of deep learning tasks by the end of this training course.

The online certification course in Deep Learning with Caffe2 offers an in-depth teaching process about the fundamentals of deep learning. Facebook open-sources Caffe2, which is a comfortable and adjustable framework for efficient deep learning. You will undergo training, based on deep learning tools, and understand the applications of Caffe2.

The Deep Learning with Caffe2 online course will provide you with the working knowledge of convolutional networks, Adam, BatchNorm, RNNs, Dropout, and more. You will establish a firm foundation in neural networks and understand how to build them. Moreover, you will train and manipulate them effortlessly by understanding Caffe2’s applications, using Python programming in various projects for Deep Learning with Caffe2 online course.

Deep Learning with Caffe2 programme provides government certification and enhances your employment possibilities in better companies. You will receive the certificate after passing the course test, with lifelong e-learning access and certification validity. 

Since the era of technology is changing, big companies are looking for new experts in various fields. The companies using modern technology require trained professionals to utilise their skills in a productive manner. Data Analytics using Keras is a part of mathematical analytics which has brought a whole new change in the technology world. It is a great way to start using digitalization and technical aspects of work in the workplace.

Nowadays, the need for such trained professionals is enhancing day by day. Big companies such as Amazon, Flipkart, Google are looking for trained professionals with a deep understanding of Keras. 

With Certified in Deep Learning with Keras, can access different skills to be professionally trained in using Keras. Online classes and supportive faculty contribute a lot to this course to be the right choice for learners seeking these skills. After getting certified through this course, learners will get several job opportunities from recruiters and other modes.

Deep learning is a modern technology that enables systems with artificial intelligence to be built that were literally impossible before. It is going to be very helpful in order to remain organised, help businesses thrive and stay on top of the market. Numerous exciting applications are currently allowed by deep learning.

PyTorch is getting popular among data science professionals. It has a clean and easy API just like Python and that will be helpful in creating neural networks much faster and easier. Candidates will be able to use PyTorch proficiently in their real world projects by the end of this Deep Learning with PyTorch programme. While pursuing this programme, candidates will be able to learn a series of tools namely, NUMPY, Cuda and others.

The course is 100 percent online and candidates can take classes at their own pace. After the completion of the course, they need to appear in an online exam to get the certificate.

Deep Learning and Reinforcement Learning Certification by Coursera introduces its learners to two of the most sought-after avenues in Machine Learning-Reinforcement Learning and Deep Learning. The latter is abundantly used to power most of the AI applications that are used on a daily basis. Deep Learning and Reinforcement Learning Certification Syllabus exhaustively cover the theory of neural networks that form the basis of Deep Learning as well as modern architectures concerned with Deep Learning. 

As an intermediate-level course, it serves as the perfect second step for aspiring data scientists interested in getting hands-on experience with both the domains in Machine Learning to learn at their own pace and earn a certification. Delivered by IBM professionals, the course will focus on Reinforcement Learning once learners have developed a few Deep Learning models. Although Reinforcement Learning has only a few practical applications at present, it is coming up as a promising area of research in AI that is expected to become relevant in the coming future. At the end of the course, data scientists will find them to be well acquainted with the learnings provided in the course. They can easily implement them in their workforce and deliver timely solutions.

Neural Networks and Deep Learning is an online certification programme available on Coursera which is offered by DeepLearning.AI, an online education technology platform with the aim of building a global community of AI talent and professionals. This programme is one of the five specializations of deep learning. 

Neural Networks and Deep Learning Certification Course is intended to assist the learners to get acquainted with fundamental concepts of neural networks and deep learning. In Neural Networks and Deep Learning Certification Syllabus, the learners will be provided with the opportunity to explore the technology of Artificial Intelligence by knowing the strategies, challenges, and outcomes of deep learning. 

Neural Networks and Deep Learning Certification by Coursera will equip the students with the skills and potential of designing and executing the deep neural networks, bring about the deep learning application in their works, apply the vectorized neural networks and understand the major technological trends in deep learning. 

Keras Training Course will help the students to make an overview of Keras which is an open-source software library that creates and gives a Python interface for artificial neural networks. In this course, the learners will dive deep into the numerous aspects of Keras such as predefined neural network layers, Installation of Keras on Docker, the usage of Keras, Multilayer Perceptron in Keras,  Neural Networks, and many more.

Administered by Mindmajix Technologies, Keras Training online course will expose the learners to the  CIFAR-10 images with DL, predefined activation functions, parameters in Neural Networks using GridSearchCV, implementing the Keras for secure application and many along with the practical training through many hands-on practical exercises and use cases. Keras Training certification can be taken by the students through different options of enrolment, namely, the corporate training, the self-study through pre-recorded videos, and online live instructor-led mode.

The stock market is renowned for its turbulence, dynamic, and nonlinear nature. Due to a variety of factors, including politics, the state of the global economy, unforeseen occurrences, a company's financial performance, and others, accurately predicting stock prices is very difficult. The Mammoth Interactive - Instructor & John Bura Web, App & Game Developer-designed the Detect Fraud and Predict the Stock Market with TensorFlow certification course, which is offered by Udemy.

Detect Fraud and Predict the Stock Market with TensorFlow online classes are intended for individuals who want to become experts in the artificial intelligence methodologies used to highlight stock market fraud. Individuals will learn about Tensorflow, linear regression, and Python in the Detect Fraud and Predict the Stock Market with TensorFlow online course, as well as about the techniques and resources needed to create stock market prediction applications.

TensorFlow Developer Certificate in 2022: Zero to Mastery online training was developed by Daniel Bourke, a machine learning engineer, writer, and video producer, and Andrei Neagoie, the founder of zerotomastery.io. Zero To Mastery is an educational platform that teaches in-demand skills and is made available through Udemy for students who want to acquire the skills to solve machine learning and deep learning problems using Tensorflow to obtain the TensorFlow developer certificate.

TensorFlow Developer Certificate in 2022: Zero to Mastery online training incorporates 63 hours of extensive lectures accompanied by 5 downloadable resources, 42 articles, and coding exercises which is intended to provide learners the opportunity to demonstrate their machine learning knowledge and experience in a global employment market that is becoming more and more AI-driven. TensorFlow Developer Certificate in 2022: Zero to Mastery online classes take learners from beginners with TensorFlow for producing excellent deep neural networks by explaining the concepts involved with deep learning, convolutional neural networks, computer vision, and natural language processing.

Google created the open-source TensorFlow library, which is primarily used for applications involving deep learning. Additionally, it claims to support conventional machine learning. Complete Guide to TensorFlow for Deep Learning with Python online certification is developed by Jose Portilla - Head of Data Science at Pierian Training which is delivered by Udemy for candidates who want to master the concepts and strategies associated with TensorFlow for deep learning activities.

Complete Guide to TensorFlow for Deep Learning with Python online course provides 14 hours of thorough lectures along with 5 downloadable learning resources and 7 articles which aim to teach the candidates about the techniques necessary to create artificial neural networks for deep learning operations. The Complete Guide to TensorFlow for Deep Learning with Python online training explains the theories behind image classification, CNN, GNN, and RNN, as well as acts as a comprehensive manual for using the TensorFlow framework following its intended purposes while demonstrating to candidates the most recent deep learning methods.

TensorFlow is an open-source framework for a variety of different machine learning problems, whereas Keras is a neural network framework. Both high-level and low-level APIs are offered by TensorFlow, whereas Keras only offers high-level APIs. Complete Tensorflow 2 and Keras Deep Learning Bootcamp certification course is designed by Jose Portilla - Head of Data Science at Pierian Training which is presented by Udemy for applicants interested in learning about TensorFlow 2 for deep learning and artificial intelligence.

Complete Tensorflow 2 and Keras Deep Learning Bootcamp online classes contain 19 hours of extensive lectures supported by 3 downloadable resources and 2 articles which guide applicants to build artificial neural networks using the TensorFlow 2 framework for deep learning operations. With Complete Tensorflow 2 and Keras Deep Learning Bootcamp online training, applicants will be taught about machine learning, natural language processing, and time series analysis as well as strategies for utilizing the Keras API to build Tensorflow 2 models more quickly.

Tensorflow is the world's most widely used deep learning framework, and it was created by Google. Tensorflow is the machine learning and artificial intelligence library of preference for many businesses. Deep Learning with TensorFlow 2.0 [2022] online certification is created by 365 Careers, an Udemy-affiliated educational platform that creates opportunities for finance and data science students.

Deep Learning with TensorFlow 2.0 [2022] online classes offers 6 hours of prerecorded lessons supported by 18 articles and 20 downloadable resources which are targeted at the students interested in mastering the strategies to code and build deep learning algorithms and machine learning algorithms from scratch to become certified data scientists. Deep Learning with TensorFlow 2.0 [2022] online training revolves around topics like neural networks, standardization, machine learning, initialization, normalization, pre-processing, training, validation, overfitting, underfitting, and more.

A large neural network library that integrates with TensorFlow is called Keras. TensorFlow is an open-sourced end-to-end framework and library for many tasks involving machine learning. A Complete Guide on TensorFlow 2.0 using Keras API certification course is developed by Hadelin de Ponteves - AI Entrepreneur, Ligency I Team - an educational organization that helps data scientists in acquiring skills & Luka Anicin AI Engineer & Entrepreneur and is made amiable by Udemy.

A Complete Guide on TensorFlow 2.0 using Keras API online training comprises 13 hours of digital lessons accompanied by 13 articles and 3 downloadable resources and is arranged to cover every topic from neural networks and training to put it in use. With A Complete Guide on TensorFlow 2.0 using Keras API online course, individuals will learn about data validation, dataset preprocessing, machine learning, CNN, ANN, and RNN as well as how to create a stock trading bot using reinforcement learning.

For building Deep Learning models, Google introduced the TensorFlow framework. Artificial neural networks are a key component of the deep learning class of machine learning models. Tensorflow Deep Learning - Data Science in Python online certification is developed by Minerva Singh- Instructor & Data Scientist and is offered by Udemy for candidates who want to master the concepts involved with TensorFlow for data science operations using python programming.

Tensorflow Deep Learning - Data Science in Python online course contains 7 hours of video-based lessons supported by 3 articles and 45 downloadable resources to provide candidates a thorough understanding of statistical modeling, data visualization, machine learning, and fundamental deep learning using the Tensorflow framework in Python. By the end of the Tensorflow Deep Learning - Data Science in Python online training, candidates will be able to use packages such as Numpy, Pandas, and Matplotlib to collaborate with actual data in Python.

The Android Machine Learning with TensorFlow lite in Java/Kotlin certification course was designed by Hamza Asif, an Android Developer, Flutter Developer, and Instructor, and is made available through Udemy, which is aimed at students who want to become proficient in the machine learning tools and methodologies to implement machine learning models in their android applications using the functionalities of TensorFlow Lite.

Android Machine Learning with TensorFlow lite in Java/Kotlin online classes encompass more than 5.5 hours of prerecorded lectures supported by 19 downloadable study materials which are geared toward teaching students how to use Android Studio and TensorFlow Lite to incorporate machine learning and computer vision into their applications for Android. Android Machine Learning with TensorFlow lite in Java/Kotlin online course discusses topics like application development, classification, and regression as well as explains the functioning of various tools like Keras, Java, Kotlin, Pandas, Numpy, and Matplotlib.

Deep learning is a branch of artificial intelligence and machine learning that resembles how learners understand specific types of information. Data science, which also includes statistical data and predictive modeling, includes deep learning as a crucial aspect. TensorFlow 101: Introduction to Deep Learning online certification is created by Sefik Ilkin Serengil - Software Engineer, which is delivered by Udemy for the participants who are interested in learning the TensorFlow framework and concepts involved with artificial intelligence, machine learning, and data science.

TensorFlow 101: Introduction to Deep Learning online training is a self-paced program that offers 4 hours of digital lessons accompanied by downloadable learning resources and assignments which is aimed at the participants who want to acquire a foundational understanding of the concepts involved with deep learning from scratch. TensorFlow 101: Introduction to Deep Learning online classes discusses topics like deep neural networks, segmentation analysis, time series analysis, supervised learning, unsupervised learning, face recognition, machine learning models, and more.

In the Full Stack Training Course, the learners will be able to learn the  Full Stack in detail and build the skills of both front-end and back-end web technologies. The online training offered by Mindmajix Technologies will facilitate the learners to become Full Stack Developers and familiarize themselves with developing web applications. 

Full Stack Training online course will take the candidates through the whole range of aspects related to Full Stack development such as web development, AngularJS & NodeJS, MongoDB, jQuery, JavaScript, and many more through real-time industry projects, namely, Creating a Web App and RESTful API Server Using the MEAN Stack and Building a beautiful Job search app using Github Jobs API. Full Stack Training certification can be accessed by the learners through three different ways of enrolment by paying the respective fees prescribed by Mindmajix.