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10 Specializations Offered by DeepLearning AI
A list of all the Specializations Offered by DeeplLearning.AI
1) AI for Good
Learn AI's role in addressing complex challenges
Build skills combining human and machine intelligence for positive real-world impact using AI.
2) Mathematics for Machine Learning and Data Science
Master the Mathematics Behind AI and Unlock Your Potential
Mathematics for Machine Learning and Data Science is a beginner-friendly specialization where you’ll master the fundamental mathematics toolkit of machine learning: calculus, linear algebra, statistics, and probability.
3) Machine Learning Specialization
Learn foundational AI concepts through an intuitive visual approach, then learn the code needed to implement the algorithms and math for ML.
4) TensorFlow: Advanced Techniques
The DeepLearning.AI TensorFlow: Advanced Techniques Specialization introduces the features of TensorFlow that provide learners with more control over their model architecture and tools that help them create and train advanced ML models. In this Specialization, you will expand your knowledge of the Functional API and build exotic non-sequential model types. You will learn how to optimize training in different environments with multiple processors and chip types and get introduced to advanced computer vision scenarios such as object detection, image segmentation, and interpreting convolutions. You will also explore generative deep learning including the ways AIs can create new content from Style Transfer to Auto Encoding, VAEs, and GANs.
5) Generative Adversarial Networks (GANs)
The DeepLearning.AI Generative Adversarial Networks (GANs) Specialization provides an exciting introduction to image generation with GANs, charting a path from foundational concepts to advanced techniques through an easy-to-understand approach. It also covers social implications, including bias in ML and the ways to detect it, privacy preservation, and more. Build a comprehensive knowledge base and gain hands-on experience in GANs. Train your own model using PyTorch, use it to create images, and evaluate a variety of advanced GANs.
6) TensorFlow: Data and Deployment Specialization
Continue developing your skills in TensorFlow as you learn to navigate through a wide range of deployment scenarios and discover new ways to use data more effectively when training your machine learning models.
In this four-course Specialization, you’ll learn how to get your machine learning models into the hands of real people on all kinds of devices. Start by understanding how to train and run machine learning models in browsers and in mobile applications. Learn how to leverage built-in datasets with just a few lines of code, learn about data pipelines with TensorFlow data services, use APIs to control data splitting, process all types of unstructured data and retrain deployed models with user data while maintaining data privacy. Apply your knowledge in various deployment scenarios and get introduced to TensorFlow Serving, TensorFlow, Hub, TensorBoard, and more.
7) TensorFlow Developer Professional Certificate
TensorFlow is one of the most in-demand and popular open-source deep learning frameworks available today. The DeepLearning.AI TensorFlow Developer Professional Certificate program teaches you applied machine learning skills with TensorFlow so you can build and train powerful models.
In this hands-on, four-course Professional Certificate program, you’ll learn the necessary tools to build scalable AI-powered applications with TensorFlow. After finishing this program, you’ll be able to apply your new TensorFlow skills to a wide range of problems and projects. This program can help you prepare for the Google TensorFlow Certificate exam and bring you one step closer to achieving the Google TensorFlow Certificate.
8) Natural Language Processing Specialization
Natural language processing is a subfield of linguistics, computer science, and artificial intelligence that uses algorithms to interpret and manipulate human language.
In the Natural Language Processing (NLP) Specialization, you will learn how to design NLP applications that perform question-answering and sentiment analysis, create tools to translate languages, summarize text, and even build chatbots. These and other NLP applications will be at the forefront of the coming transformation to an AI-powered future.
NLP is one of the most broadly applied areas of machine learning and is critical in effectively analyzing massive quantities of unstructured, text-heavy data. As AI continues to expand, so will the demand for professionals skilled at building models that analyze speech and language, uncover contextual patterns, and produce insights from text and audio.
9) Deep Learning Specialization
Looking to grow your skills and build a career in AI? Join 1 million+ learners and #BeADeepLearner with the Deep Learning Specialization, a foundational online program by machine learning pioneer Andrew Ng.
10) AI for Medicine Specialization
AI is transforming the practice of medicine. It’s helping doctors diagnose patients more accurately, make predictions about patients’ future health, and recommend better treatments. In this Specialization, you’ll gain practical experience applying machine learning to concrete problems in medicine. You’ll learn how to:
Diagnose diseases from x-rays and 3D MRI brain images
Predict patient survival rates more accurately using tree-based models
Estimate treatment effects on patients using data from randomized trials
Automate the task of labeling medical datasets using natural language processing
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The AI MARVEL Team
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