Tensor Flow

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Course Description

Post Graduate Diploma in Tensor Flow

The Famous deep learning library in the world is Google's TensorFlow. 

Google product uses machine learning in all of its products to improve the search engine, translation, image captioning or recommendations 

TensorFlow is the best library of all because it is built to be accessible for everyone.

Tensorflow library incorporates different API to built at scale deep learning architecture like CNN or RNN.

What you will learn

Who is it for?  

Fresh Grads / Professionals looking to start a career in Data Science / AI or looking for career growth into mid / senior level roles. 


Applicants should have 60% or above in X, XII and Bachelor's degree. 

The program is open for candidates in their final semester and recent graduates with 0-3 years of experience.

Candidates with a graduation in a quantitative discipline like engineering, management, mathematics, commerce, sciences, statistics, economics, etc.


Module I : What is TensorFlow? Introduction, Architecture & Example. 

Module II : How to Download and Install TensorFLow Windows and Mac. 

Module III : What is Jupyter Notebook? Complete Tutorial. 

Module IV : Torial TensorFlow Basics: Tensor, Shape, Type, Graph, Sessions & Operators.

Module V : Tensorboard Tutorial: Graph Visualization with Example. 

Module VI : Python Pandas Tutorial: Dataframe, Date Range, Slice. 

Module VII : Import CSV Data using Pandas.read_csv(). 

Module VIII : Linear Regression with TensorFlow [Examples]. 

Module IX : Linear Regression for Machine Learning. 

Module X : Linear Classifier in TensorFlow: Binary Classification Example.

Module XI : Kernel Methods in Machine Learning: Gaussian Kernel (Example). 

Module XII : Neural Network Tutorial: TensorFlow ANN Example. 

Module XIII : ConvNet(Convolutional Neural Network): TensorFlow Image Classification. 

Module XIV : Autoencoder in Deep Learning: TensorFlow Example. 

Module XV : RNN(Recurrent Neural Network) Tutorial: TensorFlow Example.

Module XVI  : Apache Spark Tutorial: Machine Learning with PySpark and MLlib. 

Module XVII : Scikit-Learn Tutorial: Machine Learning in Python. 

Topics includes 





Machine Learning 

Nerual Nertwork.

Key Program Highlights

One-on-One Mentoring 

Industry driven  curriculum 

24/7 access to study material & video lectures Live interactions

Live interactions with Data Scientists and Corporate leaders. 

Real-world Projects  & Case Studies.

Face-to-face meetup’s with top experts & your peers.

Career Guidance and support Alumni Status.

Global Certification & Alumni Status from IAADE.

Live Online Sessions.

Online Lab Sessions twice on Weekends. 

Job Assistance  &  High paid Job opportunities.

Career Prospects after completing this course

Research Engineer -  AI

Scientist -  AI 

Course Benefits:

1. Real-world projects from industry experts

2. Custom Study Plans

3. Technical Mentor Support

4. Practical tips and industry best practices

5. Personal Career Services

6. Flexible learning program

7. Additional suggested resources to improve

8. 100% Job Assistance after completion of course