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AI Deep Learning with Python

Artificial Intelligence & Deep Learning course using TensorFlow and Keras framework

This AI and Deep learning course offers practical and task-oriented training using TensorFlow and Keras on Python platform. Recent developments in Deep learning have been nothing short of a revolution and have enabled some of the most exciting and powerful applications in the field of Artificial Intelligence.  

This is a specialization course which will help you to get a break into AI and Deep Learning domain, with one of the most sought-after skills. You will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to build successful Deep Learning based AI projects using Tensor Flow and Keras. You will work on case studies on computer vision, text data processing, Image processing, Speech analytics - Speech to text / Voice tonality, IOT. After successful completion of this course you will master not only the theory, but also learn how it is applied in the industry.

Considering the practical application based curriculum, this is the best Deep Learning training course in India for Data Science professionals who are looking for an industry relevant certification from an eminent Deep Learning Institute. 

Aspirants who are want to learn Deep Learning AI training but have no prior knowledge of Data Science with Python, need to begin with either of the following 2 courses and then opt for this course as duel learning track. (You may checkout our amazing value duel course combos here!)

1. Data Science using Python (Includes Machine learning with Python)

2. Advance Big Data Science (Includes Big Data Machine learning with Python & Spark)

Artificial Intelligence and Deep Learning with Python course duration: 84 hours (36 hours Live Classes + Average 8 hours of self-study per week)

Who Should do this course?

Analytics professionals or aspirants with prior working knowledge of Data Science with Python, who are looking Deep Learning certification to up-skill with practical application of AI Deep Learning with TensorFlow and Keras.


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Course Duration 84 hours
Classes 12
Tools Python
Learning Mode Live/Video Based
Next Batch25th January, 2020 (Bangalore)

  • What are the Limitations of Machine Learning?
  • What is Deep Learning?
  • Advantage of Deep Learning over Machine learning
  • Reasons to go for Deep Learning
  • Real-Life use cases of Deep Learning
  • History of AI
  • Modern era of AI
  • How is this era of AI different?
  • Transformative Changes
  • Role of Machine learning & Deep Learning in AI
  • Hardware for AI (CPU vs. GPU vs. TPU)
  • Software Frameworks for AI
  • Deep Learning Frameworks for AI
  • Key Industry applications of AI
  • Overview of important python packages for Deep Learning
  • What is Tensor Flow?
  • Tensor Flow code-basics
  • Graph Visualization
  • Constants, Placeholders, Variables
  • Tensorflow Basic Operations
  • Linear Regression with Tensor Flow
  • Logistic Regression with Tensor Flow
  • K Nearest Neighbor algorithm with Tensor Flow
  • K-Means classifier with Tensor Flow
  • Random Forest classifier with Tensor Flow
  • Quick recap of Neural Networks
  • Activation Functions, hidden layers, hidden units
  • Illustrate & Training a Perceptron
  • Important Parameters of Perceptron
  • Understand limitations of A Single Layer Perceptron
  • Illustrate Multi-Layer Perceptron
  • Back-propagation – Learning Algorithm
  • Understand Back-propagation – Using Neural Network Example
  • TensorBoard
  • What is Deep Learning Networks?
  • Why Deep Learning Networks?
  • How Deep Learning Works?
  • Feature Extraction
  • Working of Deep Network
  • Training using Backpropagation
  • Variants of Gradient Descent
  • Types of Deep Networks
  • Feed forward neural networks (FNN)
  • Convolutional neural networks (CNN)
  • Recurrent Neural networks (RNN)
  • Generative Adversal Neural Networks (GAN)
  • Restrict Boltzman Machine (RBM)
  • Introduction to Convolutional Neural Networks
  • CNN Applications
  • Architecture of a Convolutional Neural Network
  • Convolution and Pooling layers in a CNN
  • Understanding and Visualizing a CNN
  • Transfer Learning and Fine-tuning Convolutional Neural Networks
  • Intro to RNN Model
  • Application use cases of RNN
  • Modelling sequences
  • Training RNNs with Backpropagation
  • Long Short-Term Memory (LSTM)
  • Recursive Neural Tensor Network Theory
  • Recurrent Neural Network Model
  • What is Restricted Boltzmann Machine?
  • Applications of RBM
  • Collaborative Filtering with RBM
  • Introduction to Autoencoders & Applications
  • Understanding Autoencoders
  • Define TFlearn
  • Composing Models in TFlearn
  • Sequential Composition
  • Functional Composition
  • Predefined Neural Network Layers
  • What is Batch Normalization
  • Saving and Loading a model with TFlearn
  • Customizing the Training Process
  • Using TensorBoard with TFlearn
  • Use-Case Implementation with TFlearn
  • Define Keras
  • How to compose Models in Keras
  • Sequential Composition
  • Functional Composition
  • Predefined Neural Network Layers
  • What is Batch Normalization
  • Saving and Loading a model with Keras
  • Customizing the Training Process
  • Using TensorBoard with Keras
  • Use-Case Implementation with Keras
  • Intuitively building networks with Keras
  • Computer Vision
  • Text Data Processing
  • Image processing
  • Audio & video Analytics
  • Internet of things (IOT)
  • Computer Vision
  • Text Data Processing
  • Image processing - PNG, PDF,JPEG, JPG etc.
  • Speech analytics - Speech to text / Voice tonality
  • Internet of Things - IOT

"Being a graduate from Commerce stream i was very skeptical about switching my field to analytics. There were a lot of questions that I had in my mind regarding future job prospects. All my questions were answered by Mr. Sumeet Bansal and he showed me the correct path for my future. If you wish to start your career in analytics then Alabs is the perfect choice as the faculty of Alabs have deep industry experience and currently working in the Analytics fields, they share examples with us which they face in their day to day life. The best part about the counsellors of Alabs is that they never try to sell their courses instead they would only suggest what is right for your future. Special thanks to Ankur for teaching SAS in such a way that being from a non technical background still i was able to understand the language. He will keep you engaged in the class even if you are attending the session online.The assignments and projects are very effective and it helps a lot while facing interviews I would like to mention that Alabs will be there to teach you and make you industry ready, however, the effort has to come from your side. There might be a time when you might feel that you are stuck, just stay focussed and you will do wonders. Patience is the key. Lastly I'd like to thank the whole team of Alabs for providing constant support and looking forward to join another course from your institute."

Chaitanya Relan
(Manager, American Express)

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