Certificate Course on Developing Deep Learning Applications

BY
Intel via CloudxLab

Learn to develop deep learning applications of inference using OpenVINO™ toolkit with the online Certificate Course on Developing Deep Learning Applications.

Mode

Online

Duration

6 Months

Fees

₹ 4999

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study
Mode of Delivery Video and Text Based
Learning efforts 3 Hours Per Week

Course overview

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.

The highlights

  • 100% online course
  • 6 months duration
  • Self-learning course
  • 12+ Projects
  • Certificate by Intel Corporation
  • Certificate by CloudxLab

Program offerings

  • 6 months programme
  • Online course
  • 2 completion certificates
  • Real-world projects
  • International peer community
  • Gamified learning platform
  • Timely doubts resolution
  • Intel® devcloud for the edge

Course and certificate fees

Fees information
₹ 4,999

The Certificate Course on Developing Deep Learning Applications fee is only 4,999 along with Additional Taxes Applicable (If Any). 

Certificate Course on Developing Deep Learning Applications Fee Structure

Description

Amount in Rs

Programme Fee

4,999

certificate availability

Yes

certificate providing authority

CloudxLab +1 more

Who it is for

If one is interested in concepts of deep learning application then this course will definitely interest them.

Eligibility criteria

Certification Qualifying Details

  • The Developing Deep Learning Applications certification by Intel and CloudxLab shall be offered separately. To get both the certificates, 80% completion of the course, and projects are necessary which must be within 180 days of enrollment.

What you will learn

Knowledge of deep learning

After the completion of the Certificate Course on Developing Deep Learning Applications syllabus, every student will be able to deliver high performance in applying techniques of deep learning. The students will also learn to deploy AI applications on different processors like GPUs, CPUs, and VPU in the cloud or browser. The students will be able to use these applications throughout different sectors like health, life sciences, security, manufacturing, retail, and more.

The syllabus

Module 1: Introduction to AI and OpenVINO™ Toolkit

  • AI market overview and use cases of Deep Learning 
  • Deep Learning development cycle - History, performance, and motivation 
  • Challenges in developing and deployment of Deep Learning applications at the Edge and while working with various Hardware Platforms 
  • Intel® Distribution of OpenVINO™ toolkit overview, its components and development workflow 
  • Creating an AI inference in few lines of code using OpenVINO™ toolkit 
  • Simplify and Develop for the Edge with Intel® AI Ecosystem and the various hardware and software offerings

Module 2: Setting up the Development environment for AI with OpenVINO™ Toolkit

  • AI prototyping with OpenVINO™ toolkit using Intel® DevCloud for the edge
  • Run sample applications and evaluate performance on various Intel® architecture with Intel® Devcloud for the edge
  • OpenVINO™ toolkit installation and setup on a local machine
  • Getting started in 5 minutes with OpenVINO™ toolkit using Jupyter* Notebooks
  • OpenVINO™ toolkit opensource version- Clone, Compile and Contribute
  • Intel® Edge Software Hub, a one-stop resource for optimized software and offerings for key edge use cases

Module 3: Expedite development of high-performance deep learning inference applications with Intel® Open Model Zoo

  • Introduction to Open Model Zoo and download a pre-trained model for learning or for developing deep learning software
  • Analyze various pre-trained models and public models and select an appropriate model based on the use case
  • Tools overview - Model downloader and Accuracy checker
  • Demos demonstrating various use cases with pre-trained, and public models

Module 4: Optimization and Quantization of models for better performance

  • Introduction to Model Optimizer and understand its significance 
  • Learn how model optimizer helps in streamlining the AI application development flow 
  • Model conversion overview with Model Optimizer and understanding general and framework-specific conversion parameters 
  • Generating Intermediate Representation files using Model Optimizer 
  • Convert model with general and framework-specific conversion parameters 
  • Understanding how the model optimizer works under the hood 
  • Choosing the right Quantization option in Model Optimizer based on Hardware Platform and assessing the benefits and trade-offs of using different Quantization 
  • Introduction to low precision optimization with Post-Training Optimization Tool and Understand the advantages of INT8 calibration 
  • Learn various methods to boost model performance with Post-Training Optimization Tool

Module 5: Inference Engine & integration with deep learning applications

  • Understanding various Intel® architecture - CPU, iGPU, VPU to achieve accelerated performance 
  • Introducing Intel® Movidius™ Myriad™ X VPU and getting started with Inference on Intel® Neural Compute Stick 2 
  • Hardware agnostic inference with write once deploy anywhere approach 
  • Creating powerful, scalable, and futureproof AI applications with a streamlined Development Workflow using Inference Engine 
  • Performance improvement using SYNC and ASYNC modes of the Inference Engine 
  • Efficient utilization of all the available compute resources using Heterogeneous and Multi Device Plug-ins to boost the performance

Module 6: Advanced Labs

  • Writing job file in Intel® Devcloud for the Edge and inference on multiple nodes
  • OpenVINO™ toolkit beyond vision- Speech, OCR, and NLP 
  • Using the benchmark app to estimate the inference performance of your deep learning model on various devices 
  • Advanced video analytics- Multiple models in one application 
  • Local Project Migration with Intel® DevCloud for the Edge 
  • Advanced samples and demos

Module 7: Streamline AI Application Development with Deep Learning Workbench

  • Introduction to Deep Learning Workbench and identifying the benefits 
  • Learn to create optimized AI applications using a web-based graphical environment 
  • Explore key concepts and features of Deep Learning Workbench 
  • Getting familiar with Deep Learning Workbench workflow 
  • Getting started with Deep Learning Workbench and identify the difference between running the Deep Learning Workbench on your local system and in the Intel® DevCloud for the Edge 
  • Achieve the goal of optimized AI applications, whether you are new to deep learning or an advanced deep learning developer with Deep Learning Workbench 
  • Develop and deploy optimized AI applications with Deep Learning Workbench

Module 8: Speed up the solution development journey with Intel® Edge Software Hub

  • Accelerate innovation for key edge computing use cases and starting with a powerful foundation for data processing, image processing, and edge AI analytics 
  • Selecting the vertical-specific software package, customize the configurations to your needs, and decide on your target hardware for deployment 
  • Explore the Reference Implementations to see how businesses are deploying edge intelligence in the real world
  • Downloading a Reference Implementation and Customizing it according to your requirements 
  • Simplifying the edge-to-cloud workflow integration with Intel® Edge Software Hub

Admission details

For admission to the Certificate Course on Developing Deep Learning Applications classes, one may follow these steps:

Step 1: Visit the official site: https://cloudxlab.com/course/123/certificate-course-on-developing-deep-learning-applications-offered-by-intel-corporation

Step 2: After one gets to view the ‘Enroll Now’ button, they must be making a click.

Step 3: Then, creating a new cloudxlab account is mandatory.

Step 4: After the account gets created, the next procedure is fee payment.

Step 5: The confirmed admission is only based on the fee payment and the account creation.


Filling the form

To start off, account creation is the first step to applying to this programme. The accounts can be made by the learners using only Google accounts.

How it helps

Some Certificate Courses on Developing Deep Learning Applications benefits are:

  • The learners will also be asked to participate with international peers on real-world projects.
  • The candidates receive access that is complementary to exclusive CloudxLab deep-dive courses on Python, TensorFlow,  OpenCV, Keras, and more.
  • The candidates are lucky to be certified by Intel.

Instructors

KC Rich

KC Rich
Software Program Manager
Intel Corporation

Pooja Baraskar

Pooja Baraskar
Developer Programs and Evangelism Lead
Intel Corporation

Daniel Holmlund

Daniel Holmlund
Software Engineer
Intel Corporation

Nihal Winston D’Cunha

Nihal Winston D’Cunha
Deep Learning Application Engineer
Intel Corporation

Jayakrishna Alapati

Jayakrishna Alapati
Senior Deep learning Application Engineer
Intel Corporation

Shane Ye

Shane Ye
Developer Enabler
Intel Corporation

Mr Stewart Christie

Mr Stewart Christie
Community Manager
Intel Corporation

Mr Sandeep Giri

Mr Sandeep Giri
Founder
CloudxLab

Mr Abhinav Singh

Mr Abhinav Singh
Co-Founder
CloudxLab

Mr Praveen Pavithran

Mr Praveen Pavithran
Co Founder
Freelancer

FAQs

Is any software required to be installed before starting this programme?

Yes, Intel® DevCloud for the Edge shall be installed, and 90 days of access shall also be provided.

For how long can the Certificate on Developing Deep Learning Applications online course be accessible?

Access is only allowed for 6 months from the date of enrolment.

How many certificates are to be received by the eligible participant?

2 different certificates from 2 eminent institutions shall be received.

Is there a refund policy for the Certificate Course on Developing Deep Learning Applications programme?

A full refund policy is only applicable if a student reports within the first 7 days of enrollment.

Is any kind of support given to the students?

A Community Support Forum by Intel can be approached by the learners.

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