**Deep Learning with PyTorch** training course will teach you how to develop deep learning models using Pytorch. The course will start with Pytorch's tensors and Automatic differentiation package. Then each section will cover different models starting off with fundamentals such as Linear Regression, and logistic/softmax regression. Followed by Feedforward deep neural networks, the role of different activation functions, normalization and dropout layers. Then Convolutional Neural Networks and Transfer learning will be covered.

**PyTorch - Predictive Modeling** training course will teach you how to use Pytorch for developing machine learning model for regression and classificaton. It willl also teach how to visualize the data and model using Tensorboard.

Sequential Data is the more prevalent data form such as text, speech, music, DNA sequence, video, drawing. Analysing sequential data is one of the key goals of machine learning such as document classification, time series forecasting, sentimental analysis, language translation. Seq2seq models have been used to process sequenital data. Seq2seq model has transformed the state of the art in neural machine translation, and more recently in speech synthesis. In **PyTorch - Sequential Data Modeling** training course, we will teach Seq2seq modeling with Pytorch.

Generative Models are gaining a lot of popularity recently among data scientists, mainly because they facilitate the building of AI systems that consume raw data from a source and automatically builds an understanding of it. Unlike supervised learning methods, generative models do not require labelled data. Pytorch is one of the most versatile Deep Learning to implement generative models. In **PyTorch - Generative Models** training course, you will learn how to use Pytorch for generative models.

Deep Reinforcement learning is a type of machine learning that allows machines and software agents to act smart and automatically detect the ideal behavior within a specific environment, in order to maximize its performance and productivity. Reinforcement Learning is becoming popular because it not only serves as an way to study how machine and software agents learn to act, it is also been used as a tool for constructing autonomous systems that improve themselves with experience. Pytorch is one of the most versatile Deep Learning to implement deep reinforcement learning. In **PyTorch - Deep Reinforcement** training course, you will learn how to use Pytorch for reinforcement learning.

By attending
**Deep Learning with PyTorch** workshop, delegates will learn:

- Installing Pytorch
- Math Operations with Pytorch
- Neural Networks with Pytorch
- Deep Learning with Pytorch
- Image Recognition with Convolutional Neural Network (CNN)
- Sequential Data Processing Recurrent Neural Network (RNN)

By attending
**PyTorch - Predictive Modeling** workshop, delegates will learn to:

- Understand machine learning principles to assess business insights
- Aggregate data to help test problem using Pytorch
- Apply predictive data modeling techniques to identify underlying trend and find relevant insights from the data
- Develop prototype classification model using machine learning techniques to gain new insight from data.
- Identify patterns using convolutional neural network model to derive insights and make decision
- Use Tensorboard data visualisation tool to create interactive visualizations of data

By attending
**PyTorch - Sequential Data Modeling ** workshop, delegates will learn to:

- Recap of RNN and LSTM
- 1D Convolution
- Sequence 2 Sequence Model in Pytorch
- Attention Mechanism
- Neutral Machine Translation

By attending
**PyTorch - Generative Models** workshop, delegates will learn:

- Neural Transfer Using Pytorch
- DCGAN
- Style Transfer with GAN

By attending
**PyTorch - Deep Reinforcement** workshop, delegates will learn to:

- Understand the fundamental concepts of Q Values and Q Tables
- Code Q Learning and SARSA
- Use OpenAI Gym
- Code Deep Q Network
- Code Policy Gradient

**For Deep Learning with PyTorch:**Knowledge of

- Basic Python

**For PyTorch - Predictive Modeling:**Knowledge of

- Basic Pytorch
- Basic Machine Learning

**For PyTorch - Sequential Data Modeling:**Knowledge of

- Basic Python
- Basic Pytorch
- Basic Machine Learning

**For PyTorch - Generative Models:**Knowledge of

- Python
- Pytorch
- Machine Learning

**For PyTorch - Deep Reinforcement:**Knowledge of

- Basic Python

**For Deep Learning with PyTorch && PyTorch - Predictive Modeling && PyTorch - Sequential Data Modeling courses**

- Data Scientists
- Data Analysts
- Engineers

**For - Generative Models && PyTorch - Deep Reinforcement courses**

- AI Developers
- Artificial Intelligence Engineers
- Data Scientists