Deep Learning Udacity Nanodegree Program

BEST RATED DEEP LEARNING COURSE FREE DOWNLOAD

FULL COURSE

Deep learning is driving advances in artificial intelligence that are changing our world. Enroll now to build and apply your own deep neural networks to produce amazing solutions to important challenges.

BEST RATED DEEP LEARNING COURSE FREE DOWNLOAD

FULL COURSE

*Login or Signup For Download*Deep learning is driving advances in artificial intelligence that are changing our world. Enroll now to build and apply your own deep neural networks to produce amazing solutions to important challenges.

**Become career-ready faster:**

**INDUSTRY SIZE & DEMAND**

Deep Learning Market is expected to grow at the CAGR of 52.1% till 2025

**JOB OPPORTUNITIES**

Demand for AI, DL and ML specialists in the country are expected to see a 60% rise by 2018 due to increasing adoption of automation

**RANKED #08 CNBC**

Udacity ranked as the most disruptive learning company in the world for 2 years in a row by CNBC

**GLOBAL COMMUNITY**

Join a global community of over 50,000 Deep Learning Engineers who have learned with Udacity

**COURSE CONTENT**

Best in-class content by industry leaders in the form of bite-size videos and quizzes.

**COURSE SYLLABUS**

**Introduction**

Get your first taste of deep learning by applying style transfer to your own images, and gain experience using development tools such as Anaconda and Jupyter notebooks.**Neural Networks**

Learn neural networks basics, and build your first network with Python and NumPy. Use the modern deep learning framework PyTorch to build multi-layer neural networks, and analyze real data.**Convolutional Neural Networks**

Learn how to build convolutional networks and use them to classify images (faces, melanomas, etc.) based on patterns and objects that appear in them. Use these networks to learn data compression and image denoising.**Recurrent Neural Networks**

Build your own recurrent networks and long short-term memory networks with PyTorch; perform sentiment analysis and use recurrent networks to generate new text from TV scripts.**Generative Adversarial Networks**

Learn to understand and implement a Deep Convolutional GAN (generative adversarial network) to generate realistic images, with Ian Goodfellow, the inventor of GANs, and Jun-Yan Zhu, the creator of CycleGANs.**Deploying a Sentiment Analysis Model**

Train and deploy your own PyTorch sentiment analysis model. Deployment gives you the ability to use a trained model to analyze new, user input. Build a model, deploy it, and create a gateway for accessing it from a website.

**PROJECTS**

Industry relevant projects + unlimited project reviews by our global reviewers

**PROJECT 1**

**Predicting Bike-Sharing Patterns**

Build and train neural networks from scratch to predict the number of bikeshare users on a given day.

**PROJECT 2**

**Dog-Breed Classifier**

Design and train a convolutional neural network to analyze images of dogs and correctly identify their breeds. Use transfer learning and well-known architectures to improve this model—this is excellent preparation for more advanced applications.

**PROJECT 3**

**Generate TV scripts**

Build a recurrent neural network on TensorFlow to process text. Use it to generate new episodes of your favorite TV show, based on old scripts.

**PROJECT 4**

**Generate Faces**

Build a pair of multi-layer neural networks and make them compete against each other in order to generate new, realistic faces. Try training them on a set of celebrity faces, and see what new faces the computer comes out with!

**PROJECT 5**

**Deploying a Sentiment Analysis Model**

Train and deploy your own PyTorch sentiment analysis model. You’ll build a model and create a gateway for accessing it from a website.

**Amazing Job Prospects**

Deep Learning has 1000+ jobs posted on Naukri.com in a month

**Turbocharge your salary**

Deep Learning Engineers earns an average salary in the range of INR 6-20 Lakhs In India

**Top-rated jobs**

Deep Learning engineers empower technologies like Self Driving Car, Computer Vision and many others

In this program, you’ll master deep learning fundamentals that will prepare you to launch or advance a career, and additionally pursue further advanced studies in the field of artificial intelligence. You will study cutting-edge topics such as neural, convolutional, recurrent neural, and generative adversarial networks, as well as deep reinforcement learning. You will build projects in Keras and NumPy, in addition to TensorFlow. You will learn from experts in the field, and gain exclusive insights from working professionals. For anyone interested in building expertise with this transformational technology, this Nanodegree program is an ideal point-of-entry.

If you are interested for further study in artificial intelligence, machine learning, autonomous vehicles and robotics, this Nanodegree program is the perfect way to get started!

**Before You Start:**

Educational Objectives: Become an expert in neural networks, and learn to implement them from scratch and using frameworks like PyTorch. Build convolutional networks for image recognition, recurrent networks for sequence and word generation, generative adversarial networks for image generation, and finally, learn to deploy these networks to a website.

**Prerequisite Knowledge:**

Make sure to set aside adequate time on your calendar for focused work. In order to succeed in this program, we recommend having intermediate experience with Python or at least 40hrs of programming experience using libraries like NumPy and pandas, and basic knowledge of probability will be helpful. You’ll also need to be familiar with calculus (multivariable derivatives) and linear algebra (matrix multiplication).

The Deep Learning Nanodegree program offers you a solid introduction to the world of artificial intelligence. In this program, you’ll master fundamentals that will enable you to go further in the field, launch or advance a career, and join the next generation of deep learning talent that will help define a beneficial, new, AI-powered future for our world. You will study cutting-edge topics such as Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Generative Adversarial Networks, and Network Deployment, and build projects in PyTorch and NumPy.

The program is comprised of 5 courses and 5 projects. Each project you build will be an opportunity to prove your skills and demonstrate what you’ve learned in your lessons.

This is a term-based program that requires students to keep pace with their peers. The program is delivered in 1 term spread over 4 months. On average, students will need to spend about 12-15 hours per week in order to complete all required coursework, including lecture and project time.

Length of Program: 4 months

Frequency of Classes: Term-based Number of Reviewed Projects: 5

Instructional Tools Available: Video lectures, Personalized project reviews, Interactive Jupyter notebooks,

Text instructions, Quizzes, and Question-answering platforms: Knowledge, and Study Groups

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