TechMaster - Deep Learning Fundamentals

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TechMaster - Deep Learning Fundamentals

TechMaster - Deep Learning Fundamentals

Discover what deep learning is and how it is used. Explore the concept of neural networks and learn about MapReduce, Hadoop, and YARN.

Take your first step in the fascinating world of deep learning and build sought-after skills in an important emerging technology.

Self-Paced

Mentored

BEGINNER

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This course is part of a program:

It is not possible to enroll for individual courses on this program. If you wish to take this course, please enroll for the full program.

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Deep learning enables businesses to convert large data sets into useful information and insights. It can help businesses grow, improve customer experience, and boost retention. As a branch of machine learning, deep learning applications are used in everything from self-driving cars to cancer detection monitors. Thus, within the field of artificial intelligence, deep learning is a sought-after discipline thats growing significantly in demand.

This course introduces you to deep learning and provides you with a thorough understanding of what it is and how it is used. You will explore the concept of neural networks, and you will learn about MapReduce model v1. You will consider the limitations of Hadoop 1 and MapReduce 1. You will look at the Java code required to handle the Mapper class, the Reducer class, and the program driver, YARN model. Plus, you will compare YARN, Hadoop 2, and MR2 with Hadoop 1 and MR1.

Overall, this course will take you through a holistic approach to deep learning that will address fundamental questions about deep learning is and why it matters. If you are looking to build skills in this important niche of artificial intelligence, Deep Learning Fundamentals will provide you with the ideal start you need.

This IBM certified course comprises four purposely designed modules that take you on a carefully defined learning journey.

It is a self-paced course, which means it is not run to a fixed schedule with regard to completing modules or submitting assignments. To give you an idea of how long the course takes to complete, it is anticipated that if you work 2-3 hours per week, you will complete the course in 2 weeks. However, as long as the course is completed by the end of your enrollment, you can work at your own pace. And dont worry, youre not alone! You will be encouraged to stay connected with your learning community and mentors through the course discussion space.

The materials for each module are accessible from the start of the course and will remain available for the duration of your enrollment. Methods of learning and assessment will include videos, reading material, and online exam questions.

As part of our mentoring service you will have access to valuable guidance and support throughout the course. We provide a dedicated discussion space where you can ask questions, chat with your peers, and resolve issues. Depending on the payment plan you have chosen, you may also have access to live classes and webinars, which are an excellent opportunity to discuss problems with your mentor and ask questions. Mentoring services will vary across packages.

Once you have successfully completed the course, you will earn your IBM Certificate.

After completing this course, you will be able to:

  • MapReduce model v1.
  • The limitations of Hadoop 1 and MapReduce 1.
  • The Java code required to handle the Mapper class, the Reducer class, and the program driver.
  • YARN model.
  • Comparison between YARN / Hadoop 2 / MR2 vs Hadoop 1 / MR1.

  • Machine learning engineers
  • Data scientists
  • Business intelligence analysts
  • Data quality analysts
  • Individuals keen to build their skills in deep learning

None.

Course Outline

Why Learn with SkillUp Online?

We believe every learner is an individual and every course is an opportunity to build job-ready skills. Through our human-centered approach to learning, we will empower you to fulfil your professional and personal goals and enjoy career success.

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Reskilling into tech? We’ll support you.

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Upskilling for promotion? We’ll help you.

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Cross-skilling for your career? We’ll guide you.

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Personalized Mentoring & Support

1-on-1 mentoring, live classes, webinars, weekly feedback, peer discussion, and much more.

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Practical Experience

Hands-on labs and projects tackling real-world challenges. Great for your resumé and LinkedIn profile.

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Best-in-Class Course Content

Designed by the industry for the industry so you can build job-ready skills.

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Job-Ready Skills Focus

Competency building and global certifications employers are actively looking for.

Course Offering

certificate

Type of certificate

IBM Certificate

course

About this course

04 Modules

05 Skills

includes

Includes

Discussion space

19 Videos

04 Review questions

01 Final exam

exercises

Exercises to explore

Different deep learning libraries

Vanishing gradient problem

Restricted Boltzman machines

Convolutional nets

Recurrent nets

This course has been created by

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Saeed Aghabozorgi

Sr. Data Scientist

View on LinkedIn

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FAQs

Deep learning is a subset of machine learning (ML) that uses a logical structure to process data in a way that resembles the human brain's function in order to uncover correlations and patterns. Deep learning, also known as deep neural networks, is a type of neural network that has several hidden layers, as compared to typical neural networks that have fewer layers.

In order to produce an accurate output, deep learning algorithms relate inputs to previously learned data. This technology is based on a concept that is extremely close to the way human brains work (biological neural networks).

Deep learning models are trained by utilizing vast volumes of labelled data and neural network designs that automate feature learning instead of requiring manual extraction.

This course takes a comprehensive approach to deep learning, answering basic questions about what it is, why it is important, why it is so powerful, and how to utilize it.

You will develop an understanding of convolutional neural networks. You will learn about MapReduce model v1, the limitations of Hadoop 1 and MapReduce 1, the Java code required to handle the Mapper class, the Reducer class, and the program driver YARN model. You will also compare YARN / Hadoop 2 / MR2 vs. Hadoop 1 / MR1.

Yes. This course is suitable for learners with both technical and non-technical backgrounds.

This course is self-paced, which means that you can work at a pace that suits you. It does not follow a predetermined timetable, unlike scheduled live sessions. You are free to work at your own speed if you complete the modules and the course before the deadline.

Yes, you will be issued an IBM Certificate once you have successfully completed Deep Learning Fundamentals course.

You will be able to access the course materials through your dashboard as soon as you enroll in this course.

Yes. This course is 100% online. Moreover, it is self-paced and can be completed at a speed that suits you. All you need is a good connection to the internet to access the course materials.

This IBM certified course comprises five purposely designed modules that take you on a carefully defined learning journey.

TechMaster - Deep Learning Fundamentals

Course Offering

certificate

Type of certificate

IBM Certificate

course

About this course

04 Modules

05 Skills

includes

Includes

Discussion space

19 Videos

04 Review questions

01 Final exam

exercises

Exercises to explore

Different deep learning libraries

Vanishing gradient problem

Restricted Boltzman machines

Convolutional nets

Recurrent nets

This course has been created by

profile-image

Saeed Aghabozorgi

Sr. Data Scientist

View on LinkedIn

Newsletters & Updates

Subscribe to get the latest tech career trends, guidance, and tips in your inbox.