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Deep Learning with Tensorflow
Get hands-on learning on GPU based labs to become an expert on Deep Learning and enhance your career. This is an online and web-based instructor led program with a total of 5 credit points which leads you to PG Certificate Program in AI & DL from MAHE
-
108+
learning hours -
Real-time
case studies -
Eligible for Graduates with 2+ yrs
of experience in IT/ITES
108+
learning hours
learning hours
Real-time
case studies
case studies
Eligible for Graduates with 2+ yrs
of experience in IT/ITES
of experience in IT/ITES
Ask us everything about the program
Deep Learning with Tensorflow
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Overview
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GPU Based EnvironmentAccess to a GPU-based environment and get hands-on experience in different tools. -
10+ Real-Life Case StudiesPractice on real case studies, ensures complete understanding and retention of the knowledge on each of the concepts. -
Hands-on ToolsHands-on training on Tensorflow, Scikit Learn library, Keras and other machine learning and deep learning tools. -
Live Meet-UpsGet to network with AI Experts and Enthusiasts through live meetups. -
Live InteractionsConcept explanation and implementation through live webinars and guidance by experts.
GPU Based Environment
Access to a GPU-based environment and get hands-on experience in different tools.
10+ Real-Life Case Studies
Practice on real case studies, ensures complete understanding and retention of the knowledge on each of the concepts.
Hands-on Tools
Hands-on training on Tensorflow, Scikit Learn library, Keras and other machine learning and deep learning tools.
Live Meet-Ups
Get to network with AI Experts and Enthusiasts through live meetups.
Live Interactions
Concept explanation and implementation through live webinars and guidance by experts.
About Course
Artificial Intelligence is enabling businesses to grow at a rapid pace. It is facilitating cost and time-effectiveness for them, while demanding more professionals in the field. Candidates pursuing a career in AI and DL can take up this course and fill the gap between the demand and supply of AI/DL professionals in the industry.
This course introduces you to TensorFlow, which is an open-source library by Google, for Machine Learning and Deep Learning. It is the standard tool for developing Deep Learning applications. Also, with this course, you will learn about Image Recognition and Speech Recognition using Convolution Neural Networks (CNN) and Recurrent Neural Networks (RNN).
What skills you learn
With Manipal ProLearn’s course, you will gain functional knowledge in Deep Learning and TensorFlow. The course incorporates experiential learning practices through case studies and assignments involving TensorFlow, Keras and other tools. This will help you become job-ready. You will
- Learn about Image Recognition and Speech Recognition with Deep Learning.
- Apply TensorFlow, Scikit Library and Keras to solve problems.
- Get an in-depth understanding of the use of Convolution Neural Networks (CNN) and Recurrent Neural Networks (RNN).
Who Should Attend this course
IT graduates and IT consultants willing to learn about AI and DL
IT freshers with knowledge of Python programming
IT professionals with knowledge of Machine Learning ad Text Analytics
IT professionals with knowledge of TensorFlow and Neural Networks
IT graduates and IT consultants willing to learn about AI and DL | IT freshers with knowledge of Python programming |
IT professionals with knowledge of Machine Learning ad Text Analytics | IT professionals with knowledge of TensorFlow and Neural Networks |
Key Features
Certification
After completing the course, you become certified in Deep Learning with TensorFlow; candidates with certification are preferred to those who are not certified.
Case Studies & Demo Code
Case studies and demonstrations related to real-world problems help you understand better.
Comprehensive Course Material
Concept videos, demo codes and assessments are available for access 24X7.
Request a Call Back
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Course Curriculum
1.1 Image recognition
Introduction to Image processing and Computer vision.
Convolutional Neural Networks (CNN)
Object Detection in Images
Object Detection in Video
2.1 Speech Recognition
Advance Text Analytics
Natural Language Processing
Recurrent Neural Networks- RNN
Time Series Analysis with RNN
Variations of RNN- LSTM and GRU Building and Training an RNN for Speech Recognition Developing Chatbots
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