Udacity is where lifelong learners come to learn the skills they need, to land the jobs they want, to build the lives they deserve.
Udacity is the educational organization established by Sebastian Thrun, David Stavens, and Mike Sokolsky which offers massive open online courses.
The company focuses on vocational courses for professionals.
Our mission is to train the world’s workforce in the careers of the future.
We partner with leading technology companies to learn how technology is transforming industries,
and teach the critical tech skills that companies are looking for in their workforce.
With our powerful and flexible digital education platform, even the busiest learners can prepare themselves to take on the most in-demand tech roles.
SET OF STAIRS WHICH HELP TO ATTAIN OUR MISSION
Introduction to Artificial Intelligence
Stanford University via Udacity Help
Artificial Intelligence (AI) is a field that has a long history but is still constantly and actively growing and changing. In this course, you’ll learn the basics of modern AI as well as some of the representative applications of AI. Along the way, we also hope to excite you about the numerous applications and huge possibilities in the field of AI, which continues to expand human capability beyond our imagination.
Note: Parts of this course are featured in the Machine Learning Engineer Nanodegree and the Data Analyst Nanodegree programs. If you are interested in AI, be sure to check out those programs as well!
Why Take This Course?
Artificial Intelligence (AI) technology is increasingly prevalent in our everyday lives. It has uses in a variety of industries from gaming, journalism/media, to finance, as well as in the state-of-the-art research fields from robotics, medical diagnosis, and quantum science. In this course you’ll learn the basics and applications of AI, including: machine learning, probabilistic reasoning, robotics, computer vision, and natural language processing.
Part I: Fundamentals of AI
– Overview of AI
– Statistics, Uncertainty, and Bayes networks
– Machine Learning
– Logic and Planning
– Markov Decision Processes and Reinforcement Learning
– Hidden Markov Models and Filters
– Adversarial and Advanced Planning
Part II: Applications of AI
– Image Processing and Computer Vision
– Robotics and robot motion planning – Natural Language Processing and Information Retrieval
Sebastian Thrun and Peter Norvig
Amazon , Amazon Web Services and Facebook via Udacity Nanodegree Help
In this program, you’ll cover Convolutional and Recurrent Neural Networks, Generative Adversarial Networks, Deployment, and more. You’ll use PyTorch, and have access to GPUs to train models faster. You’ll learn from authorities like Sebastian Thrun, Ian Goodfellow, Jun-Yan Zhu, and Andrew Trask. This is the ideal point-of-entry into the field of AI. 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.
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.
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.
Mat Leonard, Luis Serrano, Cezanne Camacho, Alexis Cook, Jennifer Staab, Sean Carrell, Ortal Arel, Jay Alammar, Vyom S., Peter L., Nohemy V., Sebastian P., Karim B. and Harshit A.
Become a Digital Marketer
Facebook , Google , HubSpot , Hootsuite , Moz and Mailchimp via Udacity Nanodegree Help
Meet the growing demand for skilled digital marketers by learning the latest technologies for building impactful marketing strategies.
Building a digital marketing strategy is a journey—let us be your guide. In this course, we offer a framework to help you define your business’s value proposition and branding and map out your customer journey, content strategy, and channels to achieve your business goals.
Marketing Data and Technology
In this course, you’ll learn the value of marketing data and trending technologies and how popular marketing analytics tools, such as Google Analytics, can help you understand your audience, measure the success of your acquisition, understand engagement efforts, and evaluate your user’s conversions to your goals.
Social Media Marketing (Elective)
In this course, you’ll learn more about the differences between the main social media platforms, the importance of planning, how to manage your social media presence, how to build community, leveraging organic and paid, creating effective content for multiple platforms, and actually creating 3 campaigns.
SEO Essentials (Elective)
Search engines are an essential part of the online experience. Learn how websites are optimized in search engine results using link-building, keywords, and UX design. Then conduct a search engine optimization audit in which you’ll offer recommendations for optimizing a website.
Search Engine Marketing (Elective)
Optimizing visibility in search engine results is an essential part of digital marketing. Reinforcing findability through Search Engine Marketing (SEM) is an effective tactic to achieve your marketing objectives. In this course, you’ll learn how to create, execute, and optimize an effective ad campaign using Google Ads.
Digital Advertising (Elective)
Display advertising was the first form of advertising on the web. It’s still a powerful marketing tool, strengthened by new platforms like mobile, new video opportunities, and enhanced targeting. In this course, you’ll learn how display advertising works, how it is bought and sold (including in a programmatic environment), how to set up a display/video advertising campaign using Google Ads, and strategies for effectively reaching audiences across multiple channels.
Email Marketing (Elective)
Email is an effective marketing channel, especially at the conversion and retention stage of the customer journey. In this course, you’ll learn how to create an email marketing strategy, create and execute email campaigns, and measure the results.
Anke Audenaert, Daniel Kob, Julia Aspinal, Hassan H., Ashley B., Susan L., Daniel S., Henning R. and Olivera R.
Become a Data Analyst
Kaggle via Udacity Nanodegree Help
Successful Data Analysts have a unique set of skills, and represent important value to organizations eager to make data-powered business decisions. In this program, you’ll learn to use Python, SQL, and statistics to uncover insights, communicate critical findings, and create data-driven solutions. Demand for qualified Data Analysts continues to rise, and as a graduate of this program, you will be prepared to take on these roles.Use Python, SQL, and statistics to uncover insights, communicate critical findings, and create data-driven solutions.
Introduction to Data Analysis
Learn the data analysis process of wrangling, exploring, analyzing, and communicating data. Work with data in Python, using libraries like NumPy and Pandas.
Learn how to apply inferential statistics and probability to real-world scenarios, such as analyzing A/B tests and building supervised learning models.
Learn the data wrangling process of gathering, assessing, and cleaning data. Learn to use Python to wrangle data programmatically and prepare it for analysis.
Data Visualization with Python
Learn to apply visualization principles to the data analysis process. Explore data visually at multiple levels to find insights and create a compelling story.
Josh Bernhard , Sebastian Thrun, Derek Steer, Juno Lee , Mike Yi, David Venturi, Sam Nelson, Nicholas C., Bruno A., Sagarnil D., Daniel B., Charles T. and Felix S.
Intro to Programming
University of Virginia via Udacity Help
This class will give you an introduction to the fundamentals of programming languages. Key concepts include how to specify and process valid strings, sentences and program structures.
Find and specify classes of strings using regular expressions.,Learn how to escape problematic characters.,Represent a Finite State Machine.
How to specify and deconstruct valid sentences.,Parsing grammars and discovering errors using regular expressions.,Use generators to parse strings.
Turning sentences into trees.,Discover malformed input.,Set precedence to prioritize parsing of strings.
Simulating programs.,Write an HTML interpreter.,Calling functions and interpreting function definitions.
Building a Web Browser
There are multiple more vocational courses provided by udacity.
Those who are interested in building there tech skills and want to work in this tech. field they should opt these courses from udacity.