6 Courses and Certifications

IBM Deep Learning Courses & Certifications

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Deep Learning and Reinforcement Learning

Offered by

Certificate

Deep Learning and Reinforcement Learning

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.

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9 Weeks
Intermediate
3,275
Skills Covered:
Knowledge of deep learning
Applied Deep Learning Capstone Project

Offered by

IBM via Edx
Certificate

Applied Deep Learning Capstone Project

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. 

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5 Weeks
Expert
Free
Skills Covered:
Statistical skills Data science knowledge Knowledge of deep learning
Using GPUs to Scale and Speed-up Deep Learning

Offered by

IBM via Edx
Certificate

Using GPUs to Scale and Speed-up Deep Learning

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.

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5 Weeks
Intermediate
Free
Skills Covered:
Knowledge of Artificial Intelligence Knowledge of deep learning
Deep Learning Fundamentals with Keras

Offered by

IBM via Edx
Certificate

Deep Learning Fundamentals with Keras

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. 

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5 Weeks
Intermediate
Free
Skills Covered:
Knowledge of deep learning
Specialized Models Time Series and Survival Analysis

Offered by

Certificate

Specialized Models: Time Series and Survival Analysis

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.

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3 Weeks
Intermediate
Free
Skills Covered:
Knowledge of deep learning
AI Capstone Project with Deep Learning

Offered by

Certificate

AI Capstone Project with Deep Learning

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 3 weeks and can be completely finished in around 5 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.

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3 Weeks
Expert
4,115
Skills Covered:
Machine learning Knowledge of Artificial Intelligence Knowledge of Python Knowledge of Algorithms

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