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AI Programming in C# - Beginner to Expert

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Based on 193 ratings
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Robert Gioia

The goal of this course is to take a student with little or no experience programming AI and to make them a complete master of the topic using the C# programming language.

Whether you want to:

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The goal of this course is to take a student with little or no experience programming AI and to make them a complete master of the topic using the C# programming language.

Whether you want to:

  • Build the skills you need to land your first AI development job

  • Take your career to the next level by learning AI programming for improving your productivity

  • Use your C# skills to build artificial intelligence programs

  • Understand the various algorithms that are used to make AI think and learn like a human

  • Create some exciting AI projects hands-on using the C# programming language

…this AI Programming in C# tutorial is the course you need to do all of this, and more.

Why should you learn AI Programming?

  • AI is rapidly becoming more popular worldwide, across almost all industries

  • By learning to build AI programs, you can set yourself apart and further your current career

  • With the rapid growth in AI, there are many open roles for AI developers

  • AI developers make a very lucrative salary

  • AI likely won’t take your job…but someone else who knows how to use AI better than you might

How is the course structured?

The course goes in order building up from basic to intermediate and then to advanced.

There are a total of 27 sections in the course and 14 hands-on projects that we will build step-by-step. You’ll not only gain conceptual and theoretical knowledge but also get plenty of practice putting those concepts into action using C# code.

Most sections of the course have a quiz at the end, then a video explaining the answers to the quiz questions. That means as you learn the material you will be ensuring that you grasp the key concepts and skills before moving onto the next topic.

What topics are taught in this course?

  • AI Concepts

  • Generative AI with ChatGPT

  • AI That Solves Mazes

  • Neural Networks

  • Machine Learning with ML NET

  • Hands-On: Creating a Classification AI

  • Hands-On: Building an Image Classification AI

  • Hands-On: Coding a Regression AI

  • Hands-On: Creating a Forecasting AI

  • Hands-On: Develop a Recommendation AI

  • Hands-On: Develop a Sentiment Analysis AI

  • Hands-On: Develop a Anomaly Detection AI

  • Hands-On: Develop a Text Generation AI

  • Hands-On: Develop a Time Series Analysis AI

  • Hands-On: Develop a Clustering AI

  • Hands-On: Develop a Reinforcement Learning AI

  • Data Manipulation and Analysis Fundamentals

  • Math NET Numerics for Data Analysis

  • NumSharp for Scientific Computing

  • Deedle for Time Series Data Analysis

  • Accord NET for Machine Learning and Statistical Analysis

  • ML Agents in Unity (Intelligent AI for Video Games)

  • Best Practices and Optimization

  • Appendix 1: C# Refresher

  • Appendix 2: Linear Algebra

How is this course different from the other AI courses on Udemy?

While there are plenty of AI development courses on Udemy, this course is the first one that provides a comprehensive understanding of AI programming using C#. Other courses focus on languages like Python, which is a great language that has many advantages. But if you already know C# or work a job that uses C# daily, why not learn to code AI in the language that you currently use?

This course focuses on a wide range of topics including the fundamentals of AI development, machine learning, neural networks, Chat GPT, large language models, video game AI characters, classification, regression, forecasting, recommendation, sentiment analysis, anomaly detection, text generation, time series analysis, clustering, reinforcement learning, data analysis, scientific computing, statistical analysis, AI optimization, linear algebra, and C# programming.

Are there real-world projects in this course where you can apply the skills you learn hands-on?

There are. In fact, you will build 14 hands-on AI projects in this course. You will use your C# skills to develop:

  • An AI that navigates mazes using the TorchSharp library

  • A neural network

  • A classification AI that can tell if a movie review is positive or negative

  • An image classification AI that can tell the difference between puppies and kittens

  • A regression AI that predicts housing prices

  • A forecasting AI that predicts the future prices of stocks

  • A movie recommendation AI that can suggest movies based on past viewing history

  • A sentiment analysis AI that determines if a movie review is positive, negative, or neutral

  • An anomaly detection AI that can spot anomalies in network data, like security threats

  • A text generation AI that generate Shakespearean style text based on user input

  • A time series analysis AI will be able to predict future website traffic

  • A clustering AI that groups customers into clusters based on their purchase history

  • A reinforcement learning AI that learns how to play tic tac toe

  • An artificially intelligent game character that performs collection, pathfinding, and obstacle avoidance in the Unity game engine

I will walk you through building each of these projects step by step, so don’t worry about getting overwhelmed or stuck. My students know I break down the big concepts into digestible pieces of information that anyone can understand.

Who is your instructor?

My name is Rob Gioia and I currently work as a Senior Solutions Architect in New York. C# is my favorite programming language, and most industry jobs that I have held have used C# as the primary programming language.

During my time working with C# both in the professional and personal capacity, I’ve used C# to:

  • Teach students how to program when I worked as a teacher’s assistant at the New Jersey Institute of Technology

  • Build virtual reality games to therapy children with convergence insufficiency, an eye disorder, and gamify their treatment.

  • Build a lifestyle Scratch to Win mobile app with over 10 million installs (there was some Java programming involved in this one as well :-) )

  • Develop card trader apps based around high end Intellectual Property like Marvel, Disney, and Star Wars.

  • Create Udemy courses that students have used to build full length video games using Unity and C#.

What if you have questions?

Any questions you have can be posted to the Q&A forum or messaged to me on Udemy. I check my Udemy account every day to see if students have questions, and do my best to be as responsive and helpful as possible.

If you get stuck at any point during this course, send me a message and I will get you unstuck.

There is no risk in taking this course.

This course comes with a full 30 day money-back guarantee. You either end up with C# skills, go on to develop great programs and potentially make an awesome career for yourself, or you try the course and simply get all your money back if you don’t like it…

You literally can’t lose.

Are you ready to master AI programming using the C# programming language and build an awesome set of AI development skills that can literally change your life? Then enroll now using the “Add to Cart” button on the right.

Enroll now

What's inside

Syllabus

In this section you will get introduced to the concept of AI, why we should learn to code AI, and get set up with the tools we need to follow along with the course.
Read more

This video will introduce the AI Programming in C# - Beginner to Expert course. By the end of this video you will understand the goals and learning objectives for the course.

In this video we will look at an introduction to the concept of Artificial Intelligence, or AI. By the end of this video you will understand what AI is and the role that it plays in today's technological landscape.

In this video, we will discuss reasons why you should learn to code AI. By the end of this video you will understand how learning to code AI can supercharge your career and unlock job opportunities.

In this video we will get a sneak peek at the projects that we will build in this course. By the end of this video you will understand the different projects we will be creating using C# for AI programming in this course.

In this video we will download and install Visual Studio Code with C# Dev Kit on Mac. By the end of this video you will be up and running with the program that we will write code in for this course.

In this video we will download and install Visual Studio Code with C# Dev Kit on Windows. By the end of this video you will be up and running with the program that we will write code in for this course.

This video will introduce Section 2: AI Concepts. By the end of this video you will understand what you will learn in this section of the course.

In this video we will learn about the types of AI. By the end of this video you will have an understanding of the different types of AI and the roles that they play in modern technology.

In this video we will learn about Neural Networks. By the end of this video you will understand what Neural Networks are and the role that Neural Networks play in AI development.

In this video we will learn about Machine Learning. By the end of this video you will understand what Machine Learning is, the key aspects that make up Machine Learning, and the role that machine learning plays in AI development.

In this video we will learn about Q-Learning. By the end of this video you will understand what Q-Learning is and the role that it plays in AI development.

In this video we will learn about Deep Q-Learning. By the end of this video you will understand what Deep Q-Learning is and the role that it plays in AI development.

In this video we will learn about Deep Convolutional Q-Learning. By the end of this video you will understand what Deep Convolutional Q-Learning is and the role that it plays in AI development.

In this video we will learn about Asynchronous Advantage Actor-Critic (A3C). By the end of this video you will understand what Asynchronous Advantage Actor-Critic (A3C) is and the role that it plays in AI development.

In this video we will learn about Large Language Models (LLMs). By the end of this video you will understand what Large Language Models (LLMs) are and the role that they play in AI development.

In this video we will learn about Generative AI. By the end of this video you will understand what Generative AI is and the role that it plays in AI development.

In this video we will learn about Computer Vision. By the end of this video you will understand what Computer Vision is and the role that it plays in AI development.

This quiz will test your understanding of the material taught in Section 2: AI Concepts.

In this video we will go over the answers and explanations to the quiz questions.

In this video we will look at a recap of what we learned in this section of the course. By the end of this video you will be ready to move onto the next section of the course.

In this video we will create the maze environment. By the end of this video you will have created the maze environment for the AI to navigate.

This video will introduce Section 3: Generative AI with ChatGPT. By the end of this video you will understand what you will learn in this section of the course.

In this video we will learn what ChatGPT is and the role that it plays in AI development. By the end of this video you will understand what ChatGPT is and the role that it plays in AI development.

In this video we will learn some guidelines for writing more effective ChatGPT prompts. By the end of this video you will understand how to write ChatGPT prompts more effectively.

In this video we will work on our first hands-on ChatGPT project, using ChatGPT to brainstorm ideas. By the end of this video you will have hands-on practice using ChatGPT to help you brainstorm ideas.

In this video we will work on our second hands-on ChatGPT project, using ChatGPT to write a first draft. By the end of this video you will have hands-on practice using ChatGPT to write a first draft.

In this video we will work on our third hands-on ChatGPT project, using ChatGPT to create a personalized workout plan. By the end of this video you will have hands-on practice using ChatGPT to create a personalized workout routine.

In this video we will work on our fourth hands-on ChatGPT project, using ChatGPT to summarize a book. By the end of this video you will have hands-on practice using ChatGPT to summarize a book.

In this video we will work on our fifth hands-on ChatGPT project, using ChatGPT to write code. By the end of this video you will have hands-on experience using ChatGPT to write code.

This quiz will test your understanding of the material taught in Section 3: Generative AI with ChatGPT.

In this video we will code the Neural Network class. By the end of this video we will have begun creating the Neural Network using C# code.

This video will introduce Section 4: AI That Solves Mazes. By the end of this video you will understand what you will learn in this section of the course.

In this video we will learn what TorchSharp is. By the end of this video you will understand what TorchSharp is and the role that it plays in AI development with C#.

In this video we will implement the actions and rewards for the AI that solves mazes program. By the end of this video you will have implemented the actions and rewards for the maze AI that we are building in this section.

In this video we will train the model. By the end of this video you will have a trained AI model.

In this video we will visualize the final results of our AI navigating the maze. By the end of this video you will have completed an AI programming project.

This quiz will test your understanding of the material taught in Section 4: AI That Solves Mazes.

This video will introduce Section 5: Neural Networks. By the end of this video you will understand what you will learn in this section of the course.

In this video we will learn what a neural network is. By the end of this video you will understand what Neural Networks are and the role that they play in AI development.

In this video we will learn about the architecture of a Neural Network. By the end of this video you will understand Neural Network architecture and the role that it plays in AI development.

In this video we will get a sneak peek of the Neural Network program that we will create in this section of the course. By the end of this video you will have a clear understanding of the Neural Network project we will build using C# code.

In this video we will code the Activate function. By the end of this video you will understand the role that the Activate (Sigmoid) function plays in Neural Networks and how to implement this type of function in C#.

In this video we will code the Train function. By the end of this video you will understand how to train an AI model using C# code.

In this video we will code the Dot Product function. By the end of this video you will understand what the term dot product means and how to obtain the dot product between 2 matrices using C# code.

In this video we will code the Perform Operation function. By the end of this video you will understand how to write a function that performs mathamatical operations on 2 matrices.

In this video we will code the Transpose function. By the end of this video you will understand what it means to transpose a matrix, or 2D array, and have experience writing a function to transpose a matrix using C# code.

In this video we will test our code and visualize the results of the program. By the end of this video you will have viewed our C# neural network in action.

In this video we will learn about the real world applications of neural networks. By the end of this video you will understand how neural networks are used in the real world and the role that they play in AI development.

This quiz will test your understanding of the material taught in Section 5: Neural Networks.

This video will introduce Section 6: Machine Learning with ML.NET. By the end of this video you will understand what you will learn in this section of the course.

In this video we will learn what ML.NET is. By the end of this video you will understand what ML.NET is and the role that it plays in AI development.

In this video we will setup ML.NET. By the end of this video you will have ML.NET set up on your computer and be ready to begin using it for AI development.

In this video we will learn the basics of machine learning with ML.NET, including its capabilities and key concepts. By the end of this video, you will understand how ML.NET can be used for various machine learning tasks and its importance in building predictive models.

In this video we will learn how to prepare and load data into ML.NET for machine learning tasks, covering techniques for data preprocessing and cleaning. By the end of this video, you will be able to effectively load and preprocess data to prepare it for model training in ML.NET.

In this video, we will learn about feature engineering techniques in ML.NET, including feature selection and extraction methods for improving model performance. By the end of this video, you will know how to handle categorical and numerical features and perform feature engineering to enhance your machine learning models in ML.NET.

In this video, we will learn how to select and evaluate machine learning models in ML.NET, covering techniques for choosing the right model and evaluating its performance. By the end of this video, you will be able to select appropriate models for your tasks and evaluate their performance using metrics like accuracy, precision, and recall in ML.NET.

In this video, we will learn how to train and tune machine learning models in ML.NET, including techniques for model training and hyperparameter tuning. By the end of this video, you will know how to train models effectively and optimize their performance through hyperparameter tuning in ML.NET.

In this video, we will learn how to deploy and integrate machine learning models into applications using ML.NET, covering techniques for deploying models to production environments and integrating them into C# applications. By the end of this video, you will know how to deploy trained models and use them to make predictions in real-world applications with ML.NET.

This quiz will test your understanding of the material taught in Section 6: Machine Learning with ML.NET.

This video will introduce Section 7: Hands-On: Creating a Classification AI. By the end of this video you will understand what you will learn in this section of the course.

In this video we will learn about Classification. By the end of this video you will understand what Classification is and the role that it plays in AI development.

In this video we will get a sneak peek at the classification AI we will create hands-on in this section using ML.NET and C#.

In this video we will create the project for our classification AI. By the end of this video you will have a project set up for the classification AI that we will build in this section of the course.

In this video we will set up the data for the classification AI. By the end of this video you will have set up the data for the classification AI program we will build in this section of the course.

In this video we will load the data for our classification AI. By the end of this video you will have loaded the data for the classification AI.

In this video we will train the model for our classification AI. By the end of this video we will have trained a classification AI model.

In this video we will evaluate and test the model for our classification AI. By the end of this video we will have evaluated and tested our classification AI model.

This quiz will test your understanding of the material taught in Section 7: Hands-On: Creating a Classification AI.

This video will introduce Section 8: Hands-On: Building an Image Classification AI. By the end of this video you will understand what you will learn in this section of the course.

In this video we will learn about Image Classification. By the end of this video you will understand what Image Classification is and the role that it plays in AI development.

In this video we will get a sneak peek at the image classification AI we will create hands-on in this section using ML.NET and C#.

In this video we will create the project for our image classification AI. By the end of this video you will have a project set up for the image classification AI that we will build in this section of the course.

In this video we will set up the data for the image classification AI. By the end of this video you will have set up the data for the image classification AI program we will build in this section of the course.

In this video we will load the data for our image classification AI. By the end of this video you will have loaded the data for the image classification AI.

In this video we will train the model for our image classification AI. By the end of this video we will have trained a image classification AI model.

In this video we will evaluate and test the model for our image classification AI. By the end of this video we will have evaluated our image classification AI model.

This quiz will test your understanding of the material taught in Section 8: Hands-On: Building an Image Classification AI.

This video will introduce Section 9: Hands-On: Coding a Regression AI. By the end of this video you will understand what you will learn in this section of the course.

In this video we will learn about Regression. By the end of this video you will understand what Regression is and the role that it plays in AI development.

Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Focuses on C#, which allows developers already familiar with the language to apply their existing skills to AI development without needing to learn a new language
Begins with fundamental AI concepts and gradually progresses to intermediate and advanced topics, making it suitable for learners with little to no prior experience
Includes a C# refresher in the appendix, which is helpful for those who may need to brush up on their C# skills before diving into AI-specific topics
Covers a wide range of AI topics, including machine learning, neural networks, ChatGPT, and video game AI, providing a comprehensive overview of the field
Features 14 hands-on AI projects, which allows learners to apply their knowledge and build a portfolio of AI applications using C#
Uses ML.NET, Accord.NET, NumSharp, Deedle, and TorchSharp, which may require learners to install additional libraries and dependencies

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Reviews summary

Mastering ai development with c#

Based on the course description and syllabus, this course aims to take learners from beginner to expert in AI programming using C#. It promises a comprehensive understanding covering core concepts like neural networks and machine learning with ML.NET, through to advanced topics. A key feature is the inclusion of 14 hands-on projects using C# for various AI tasks, from maze solving with TorchSharp to image classification and Unity game AI. The course is structured step-by-step with quizzes and aims to distinguish itself by focusing specifically on the C# language. As actual student reviews were not provided, this analysis is based solely on the course's advertised content and structure.
Covers fundamental to advanced AI concepts.
"The goal of this course is to take a student with little or no experience programming AI and to make them a complete master..."
"The course goes in order building up from basic to intermediate and then to advanced."
Covers various AI types and C# libraries.
"This course focuses on a wide range of topics including the fundamentals of AI development, machine learning, neural networks...and C# programming."
"You will use your C# skills to develop: An AI that navigates mazes using the TorchSharp library... A neural network... A classification AI..."
"...machine learning with ML.NET... Math NET Numerics... NumSharp... Deedle... Accord NET... ML Agents in Unity..."
Learn by building 14 diverse AI projects.
"There are a total of 27 sections in the course and 14 hands-on projects that we will build step-by-step."
"You’ll not only gain conceptual and theoretical knowledge but also get plenty of practice putting those concepts into action using C# code."
"Are there real-world projects in this course where you can apply the skills you learn hands-on? There are. In fact, you will build 14 hands-on AI projects..."
Leveraging C# for AI development.
"this course is the first one that provides a comprehensive understanding of AI programming using C#."
"if you already know C# or work a job that uses C# daily, why not learn to code AI in the language that you currently use?"
"Use your C# skills to build artificial intelligence programs"
"C# is my favorite programming language, and most industry jobs that I have held have used C# as the primary programming language."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in AI Programming in C# - Beginner to Expert with these activities:
Review C# Fundamentals
Solidify your understanding of C# syntax and core concepts before diving into AI-specific applications.
Browse courses on C# Programming
Show steps
  • Review C# data types, variables, and operators.
  • Practice writing simple C# programs.
  • Familiarize yourself with C# control flow statements.
Review: 'C# 10 and .NET 6 - Modern Cross-Platform Development'
Gain a solid understanding of C# concepts and syntax before working on the hands-on projects.
View C# 10 and .NET 6 – Modern Cross-Platform... on Amazon
Show steps
  • Read the book and take notes on key concepts.
  • Try out the code examples provided in the book.
  • Relate the concepts to the course syllabus.
Review: 'Machine Learning.NET Succinctly'
Gain a solid understanding of ML.NET concepts and syntax before working on the hands-on projects.
View Putting Knowledge to Work on Amazon
Show steps
  • Read the book and take notes on key concepts.
  • Try out the code examples provided in the book.
  • Relate the concepts to the course syllabus.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Implement a Simple Neural Network
Solidify your understanding of neural networks by building a basic one from scratch in C#.
Show steps
  • Design the architecture of your neural network.
  • Implement the forward and backward propagation algorithms.
  • Train the network on a simple dataset.
  • Evaluate the performance of your network.
Practice Linear Algebra Problems
Reinforce your understanding of linear algebra concepts, which are fundamental to many AI algorithms.
Show steps
  • Solve matrix multiplication problems.
  • Calculate eigenvalues and eigenvectors.
  • Practice vector operations.
Blog Post: AI Applications in C#
Deepen your understanding of AI by researching and writing about real-world applications of AI in C#.
Show steps
  • Research different AI applications implemented in C#.
  • Choose a specific application to focus on.
  • Write a blog post explaining the application and its implementation.
  • Publish your blog post online.
Contribute to an ML.NET Project
Enhance your skills and contribute to the AI community by contributing to an open-source ML.NET project.
Show steps
  • Find an open-source ML.NET project on GitHub.
  • Identify an issue or feature to work on.
  • Submit a pull request with your changes.
  • Respond to feedback and iterate on your changes.

Career center

Learners who complete AI Programming in C# - Beginner to Expert will develop knowledge and skills that may be useful to these careers:
Artificial Intelligence Programmer
An Artificial Intelligence Programmer designs, develops, and implements AI solutions. They possess expertise in programming languages, algorithms, and machine learning techniques. This course, designed for students with little to no AI programming experience, helps build a strong foundation in AI programming using C#. You will learn core AI concepts and gain experience with machine learning, neural networks, and generative AI. Moreover, the course covers several AI projects using C#, providing hands-on experience with AI development. Skills acquired in this course help to build an excellent portfolio that leads to a successful transition into the artificial intelligence programmer role.
See salaries and explore the career path for Artificial Intelligence Programmer
AI Developer
An AI Developer focuses on creating artificial intelligence applications. They are proficient in programming languages, machine learning, and neural networks. This course aims to transform students with little to no prior experience into AI experts using C#. You will explore topics such as generative AI with ChatGPT, neural networks, and machine learning with ML.NET. The hands-on projects, including developing anomaly detection, text generation, time series analysis, and clustering AIs, provide valuable experience. The course can lead to a successful transition into an AI developer role.
See salaries and explore the career path for AI Developer
Machine Learning Engineer
A Machine Learning Engineer develops algorithms that allow computers to learn from data. They are responsible for designing, building, and deploying machine learning models. This course provides a comprehensive introduction to machine learning using C#, covering topics such as neural networks and machine learning with ML.NET. The hands-on projects, including creating classification, image classification, regression, forecasting, and recommendation AIs, provide practical experience that helps build a strong portfolio. Learning AI programming in C# can set you apart and further your career as a machine learning engineer.
See salaries and explore the career path for Machine Learning Engineer
Data Scientist
A Data Scientist analyzes large datasets to extract meaningful insights and inform decision-making. They often use machine learning techniques to build predictive models. By taking on a data scientist role, you will learn the fundamentals of artificial intelligence development. This course helps by covering data manipulation, analysis, and machine learning with ML.NET. You will develop critical skills in data analysis, scientific computing, and statistical analysis. By building real-world projects, your portfolio will demonstrate your competence as a data scientist.
See salaries and explore the career path for Data Scientist
Game Developer
A Game Developer creates video games for various platforms. AI is often used to create intelligent non-player characters (NPCs) and enhance gameplay. This course helps in game development, particularly with the section on ML Agents in Unity. You can create intelligent AI for video games. The hands-on project of developing an AI game character that performs pathfinding and obstacle avoidance directly enhances your game development capabilities. This allows you to design more engaging and realistic game environments as a game developer.
See salaries and explore the career path for Game Developer
Software Engineer
A Software Engineer designs, develops, and tests software applications. They can specialize in various areas, including AI. You can set yourself apart by building AI programs that further your career as a software engineer. This course helps build expertise in AI programming using C#, covering key aspects like machine learning, neural networks, and generative AI. The hands-on projects, such as creating an AI that solves mazes and building image classification AIs, provide practical skills. Learning AI programming helps integrate artificial intelligence into various software projects.
See salaries and explore the career path for Software Engineer
Solutions Architect
A Solutions Architect designs and oversees the implementation of technology solutions. They need a broad understanding of various technologies, including AI. You can develop solutions to problems using C#, or the programming language used daily in your job. This course helps you understand AI concepts, generative AI, and machine learning with ML.NET. The best practices and optimization techniques covered in the course, combined with hands-on projects, position you exceptionally well. This course helps you create effective AI solutions as a solutions architect.
See salaries and explore the career path for Solutions Architect
Data Analyst
A Data Analyst interprets data and transforms it into actionable insights. They work with data to identify trends, patterns, and anomalies. This course may be useful by providing a strong foundation in data manipulation and analysis using tools like Math NET Numerics, NumSharp, and Deedle. By learning these technologies, you enhance your ability to analyze complex datasets and make informed decisions. The skills provided here can help integrate you as a data analyst even when you don't have an extensive background in machine learning.
See salaries and explore the career path for Data Analyst
AI Consultant
An AI Consultant advises organizations on how to implement AI solutions to improve their business processes. This may be a good fit as it provides a comprehensive understanding of AI programming using C#. The course covers a wide range of topics, including machine learning, neural networks, and ChatGPT. The wide coverage of topics here, combined with the hands-on projects like developing recommendation and sentiment analysis AIs, provides practical experience that enables you to offer valuable guidance to clients. This course may be useful in preparing you to become a successful AI consultant.
See salaries and explore the career path for AI Consultant
Research Scientist
A Research Scientist conducts research to advance knowledge in a specific field, such as artificial intelligence. A research scientist often needs an advanced degree (master's or phd). This course may be useful in providing a strong foundation in AI concepts, machine learning, and neural networks. The course also covers essential mathematical concepts, which can assist in research. This expertise, combined with hands-on experience from building AI projects, supports your capability to contribute to cutting-edge research in AI as a research scientist.
See salaries and explore the career path for Research Scientist
AI Trainer
An AI Trainer is responsible for training and fine-tuning AI models to improve their accuracy and performance. You can improve your productivity by learning how to create AI programs. This course helps build a deep understanding of machine learning, neural networks, and generative AI. The hands-on projects, such as creating classification, image classification, and regression AIs, provide practical skills in model development. The skills you will learn may be useful in helping to train different types of AI models effectively as an AI trainer.
See salaries and explore the career path for AI Trainer
Robotics Engineer
A Robotics Engineer designs, builds, and programs robots for various applications. This course may be helpful by covering AI concepts and machine learning techniques that are applicable to robotics. Even though the focus is on C#, the programming and algorithmic principles learned can be adapted to robotics programming languages. This knowledge, combined with your robotics expertise, enhances your ability to develop intelligent and autonomous robots. You will be able to contribute to robotics projects as a robotics engineer.
See salaries and explore the career path for Robotics Engineer
Technology Consultant
A Technology Consultant advises businesses on how to use technology to meet their goals. This course may be useful in understanding AI programming, machine learning, and neural networks. Even though this course is specifically in the C# language, it can provide useful insight for one who wishes to advise on AI products. In particular, the coverage of generative AI with ChatGPT and the different AI project types may be particularly insightful for a consultant.
See salaries and explore the career path for Technology Consultant
Business Intelligence Analyst
A Business Intelligence Analyst analyzes data to identify trends and insights that inform business decisions. They may use data to create reports and dashboards. This course may be useful because it helps build a foundation in data manipulation and analysis, as well as machine learning concepts. This knowledge, even if not directly applied in C#, enhances your ability to understand and interpret complex data trends and patterns. You will be able to make better business decisions as a result.
See salaries and explore the career path for Business Intelligence Analyst
Technical Support Engineer
A Technical Support Engineer provides technical assistance to customers and helps resolve technical issues. This role may be useful because it helps build a solid understanding of AI programming concepts and machine learning techniques. This knowledge, even if not directly used for coding, enhances your ability to troubleshoot AI-related problems, explain technical details to customers, and provide effective solutions. The course will help you be a more effective technical support specialist.
See salaries and explore the career path for Technical Support Engineer

Reading list

We've selected two books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in AI Programming in C# - Beginner to Expert.
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Putting Knowledge to Work
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Provides a concise introduction to machine learning using the ML.NET library. It covers essential concepts and practical examples, making it a valuable resource for understanding the ML.NET framework. It is particularly useful for those who are new to machine learning and want to quickly get up to speed with the basics. This book good reference for the Machine Learning with ML.NET section of the course.
Putting Knowledge to Work
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Putting Knowledge to Work
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C# 10 and .NET 6 – Modern Cross-Platform Development
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Provides a comprehensive guide to C# 10 and .NET 6, covering the latest features and best practices for modern C# development. It valuable resource for understanding the C# language and the .NET ecosystem. It is particularly useful for those who want to stay up-to-date with the latest C# features. This book good reference for the C# refresher section of the course.
C# 10 and .NET 6 – Modern Cross-Platform Development
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C# 10 and .NET 6 – Modern Cross-Platform Development
Kindle Edition
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Rating
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Effort
16 total hours
Via
Udemy
Instructor
Robert Gioia
Language
English
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Focuses on C#, which allows developers already familiar with the language to apply their existing skills to AI development without needing to learn a new language
Begins with fundamental AI concepts and gradually progresses to intermediate and advanced topics, making it suitable for learners with little to no prior experience
Includes a C# refresher in the appendix, which is helpful for those who may need to brush up on their C# skills before diving into AI-specific topics
Covers a wide range of AI topics, including machine learning, neural networks, ChatGPT, and video game AI, providing a comprehensive overview of the field
Features 14 hands-on AI projects, which allows learners to apply their knowledge and build a portfolio of AI applications using C#
Uses ML.NET, Accord.NET, NumSharp, Deedle, and TorchSharp, which may require learners to install additional libraries and dependencies
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