This course is for a complete novice of Python coding, so no prior knowledge or experience in software coding is required. This course selects, introduces and explains Python syntaxes, functions and libraries that were frequently used in AI coding. In addition, this course introduces vital syntaxes, and functions often used in AI coding and explains the complementary relationship among NumPy, Pandas and TensorFlow, so this course is helpful for even seasoned python users. This course starts with building an AI coding environment without failures on learners’ desktop or notebook computers to enable them to start AI modeling and coding with Scikit-learn, TensorFlow and Keras upon completing this course. Because learners have an AI coding environment on their computers after taking this course, they can start AI coding and do not need to join or use the cloud-based services.

What you will learn

Describe the benefits of implementing AI in organizations, in terms of context, problems, research approach and results.
Identify the implications of implementing AI in terms of improvement strategies for organizations in industry, academia and education.
Understand the aspects of AI compliance and ethics and their significance for your own organization.
Create a plan for the application of AI in your own organization.

What you will learn

A broad and robust understanding of computer science and programming
Graph search algorithms
Reinforcement learning
Machine learning
Artificial intelligence principles
How to design intelligent systems
How to use AI in Python programs

What you will learn

Understand AI basics, its applications and use cases, and how its transforming our lives.
Identify various Watson AI services from IBM and what they can be used for.
Describe how AI-powered chatbot technology works and its applications.
Experience hands-on interactions with several AI environments and applications.
Build and deploy an AI enabled chatbot on a website – without any coding.

Artificial intelligence (AI) is transforming our world. Whether you’re a student, a developer, or a technology consultant - understanding AI and knowing how to create AI-powered applications can give you an edge in your career. This Professional Certificate is designed to arm you with the skills to work as an AI developer.

This program will give you a firm understanding of AI technology, its applications, and its use cases. You will become familiar with concepts and tools like machine learning, data science, natural language processing, image classification, image processing, IBM Watson AI services, OpenCV, and APIs. Even if you have no programming background, through this Professional Certificate, you will learn practical Python skills to design, build, and deploy AI applications on the web. The courses will also enable you to apply pre-built AI smarts to your products and solutions.

Rather than create complex AI algorithms and interfaces from scratch, you’ll use IBM Watson AI services and APIs to create smart applications with minimal coding. By the end of this Professional Certificate, you will have completed several projects that showcase proficiency in applying AI and building AI-powered solutions.

In addition to earning a Professional Certificate from Coursera, you'll also receive a digital badge from IBM recognizing your proficiency in applied AI.

Many people have big data but only some people know what to do with it. Why? Well, the big problem is that the data is big—the size, complexity and diversity of datasets increases every day. This means we need new solutions for analysing data.

This course equips you for working with these solutions by introducing you to selected statistical and machine learning techniques used for analysing large datasets and extracting information. We also expose you to three software packages so you can develop your coding skills by completing practical exercises.

Self-Driving Cars with Duckietown is the first robotics and AI MOOC with scale-model self-driving cars. Learn state-of-the-art autonomy hands-on: build your own real robot (Duckiebot) and get it to drive autonomously in your scaled city (Duckietown).

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.

Ready to deploy your models to the world? Learn how to go live with your models with the TensorFlow: Data and Deployment Specialization.

Looking to customize and build powerful real-world models for complex scenarios? Check out the TensorFlow: Advanced Techniques Specialization.

Проект прикладного обучения

In the DeepLearning.AI TensorFlow Developer Professional Certificate program, you'll get hands-on experience through 16 Python programming assignments. By the end of this program, you will be ready to:

- Build and train neural networks using TensorFlow

- Improve your network’s performance using convolutions as you train it to identify real-world images

- Teach machines to understand, analyze, and respond to human speech with natural language processing systems

- Process text, represent sentences as vectors, and train a model to create original poetry!

Do your non-player characters (NPCs) lack drive and ambition? Are they slow, stupid and constantly banging their heads against the wall? Then this course is for you. Join Penny as she explains, demonstrates and assists you in creating your very own NPCs in Unity with C#. All you need is a sound knowledge of Unity, C# and the ability to add two numbers together.
This course uses Unity Version 2021.3 LTS
In this course, Penny reveals the most popular AI techniques used for creating believable character behaviour in games using her internationally acclaimed teaching style and knowledge from over 30 years working with games, graphics and having written two award winning books on games AI. Throughout, you will follow along with hands-on workshops designed to teach you about the fundamental AI techniques used in today's games. You'll join in as NPCs are programmed to chase, patrol, shoot, race, crowd and much more.
Learn how to program and work with:

vectors

waypoints

navmeshes

the A* algorithm

crowds

flocks

animated characters

vehicles

and industry standard techniques such as goal-oriented action learning and behaviour trees.

Contents and Overview
The course begins with a detailed examination of vector mathematics that sits at the very heart of programming the movement of NPCs. Following this, systems of waypoints will be used to move characters around in an environment before examining the Unity waypoint system for car racing with AI controlled cars. This leads into an investigation of graph theory and the A* algorithm before we apply these principles to developing navmeshes and developing NPCs who can find their way around a game environment. Before an aquarium is programmed complete with autonomous schooling fish, crowds of people will be examined from the recreation of sidewalk traffic, to groups of people fleeing from danger. Having examined the differing ways to move NPCs around in a game environment, their thinking abilities will be discussed with full explanations and more hands-on workshops using finite state machines and behaviour trees.
The follow-along workshops included in the course come with starter Unity asset files and projects complete with solutions. Throughout, there are also quizzes and challenge exercises to reinforce your learning and guide you to express your newfound knowledge.

At the completion of this course you will have gained a broad understanding of what AI is in games, how it works and how you can use it in your own projects. It will equip you with a toolset to examine any of the techniques presented in more depth to take your game environments to the next level.

What students are saying about this course:

This has been my favourite Udemy-Unity course so far. It took me from literally 0% knowledge of how game AI is achieved, and took me to a whole new level. Waypoints, pathfinding, state machines, etc etc etc are all covered in-depth and will reveal the magic (spoiler alert: it isn't magic) behind making your computer characters seem like they really have a mind of their own.

Oh My God. I love her way of teaching things. I haven’t finished this course yet. But all i can say is that it is another brilliant course from her. Artificial intelligence by itself is a tricky thing to do. And before starting this course i never thought that i will understand anything in it. But i was wrong. With her style of teaching, you will learn how to move your characters in an ”intelligent“ way. This course is perfectly sliced and the pace is wonderful.

This is the legendary Titanic ML competition – the best, first challenge for you to dive into ML competitions and familiarize yourself with how the Kaggle platform works.

The competition is simple: use machine learning to create a model that predicts which passengers survived the Titanic shipwreck.

Read on or watch the video below to explore more details. Once you’re ready to start competing, click on the "Join Competition button to create an account and gain access to the competition data. Then check out Alexis Cook’s Titanic Tutorial that walks you through step by step how to make your first submission!

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