LIVE Online AI Training - Tensorflow for Developer Certification 

The mission of the Boston Training Academy (BTA) is to become a renowned developmental ground for talent engagement, education and solutions across a variety of disciplines. The BTA offers structured, face-to-face, labs and training delivered by world-class trainers that are tailored to the knowledge-base of the attendees.

Boston Training Academy

Please note: The dates for this course are on a first come first served basis . If this date fills up then an altertaive date will be provided to you. 
 
Now is the time to up-skill and re-skill!
The Boston Training Academy (BTA) is pleased to launch LIVE and Fully Interactive instructor-led learning, presented by leading industry expert trainers with practical labs at your desk - so no need to travel or change your schedule!
These bite-size courses are a great opportunity to further your professional development with project-ready skills wherever you are, without losing touch with your work commitments at affordable prices. 
These courses are ideal for anyone who is looking to up-skill from an Engernerring, Science, AI, DL background. 
On completion of the course, participants will be awarded a certification from the Boston Training Academy and a digital badge for your social media.
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Course Overview:
Understand the foundational principles of Machine Learning (ML) and Deep Learning (DL).
Learn how to build ML models using TensorFlow the industry's most predominantly used tool.
Build your own image recognition, object detection, text recognition algorithms with deep neural networks and convolutional neural networks.
Use real-world images in different shapes and sizes to visualize the journey of an image through convolutions to understand how a computer “sees” information, plot loss and accuracy.
Explore strategies to prevent over-fitting, including augmentation and dropouts and, apply neural networks to solve natural language processing problems using TensorFlow.
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Foundational principles of ML and Deep Learning
</LI>
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Building ML models in TensorFlow
</LI>
<LI>
Building image recognition, object detection, text recognition algorithms with deep neural networks and convolutional neural networks
</LI>
<LI>
Using real-world images in different shapes and sizes to visualize the journey of an image through convolutions to understand how a computer “sees” information, plot loss and accuracy
</LI>
<LI>
Exploring strategies to prevent overfitting, including augmentation and dropouts
</LI>
<LI>
Applying neural networks to solve natural language processing problems using TensorFlow
</LI>
</UL>
PRE-REQUISITES: Basic Python, C/C++ or Java
Technical Pre-requsites: 
Should Install Tensorflow Module 
Knowledge in Basic Python is a must
Should Knowledge in anyone programming Language like C/C++, Java, R
Zeal to become a developer on TensorFlow Framework 
Any Education Background
Hardware:
Recommended Specifications:
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Processor: Intel i5 7th Generations or Higher
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RAM: 8GB
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Graphic Card: Not Required if you have it a bonus
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Storage: 512 GB
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</UL>
Minimum Specification:
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Processor: Intel i3 7th Generations or Higher
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RAM: 4GB
</LI>
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Graphic Card: Not Required
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Storage: 256 TB
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</UL>
Software:
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Anaconda with Intel Python
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OS: Windows* Linux* macOS*
</LI>
</UL>
Medium of Instruction: English
Mode of Delivery: Online Live Instructor Led Session
Note: This course is designed to run on Intel Processor Family if you don’t have just use Google Colab
Process to Sign up for Colab
Anyone with a Google Drive account can sign up for Colab by heading to <A HREF="http://www.colab.research.google.com/" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">www.colab.research.google.com</A> and following the listed instructions.
We look forward to welcoming you onto our course! 
Disclaimer: When registering onto this course, you consent for Boston Limited to send you information on similar courses we may be running. Your details will not be forwarded over to any third parties. 
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LIVE Online AI Training - Tensorflow for Developer Certification

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