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It's the new year. You want to achieve your goals. Do you want to explore something new? Do you want to change careers? But it can be overwhelming.
You don't know where to start. You don't know which course is best for you to achieve your professional goals. You're not sure which route to take first. It can be too overwhelming.
This blog is here to help.
Let's say you're making a career change, specifically related to ai. You came to the right page. Microsoft has some really great FREE resources to help you get where you need them.
Absorbing all the free content you can will be your best first option, before jumping into paying for a course or going back to university. Free resources will help you evaluate whether this is what you really want to do.
Link: ai-For-Beginners/” rel=”noopener” target=”_blank”>ai for beginners
Microsoft offers a 12-week, 24-lesson curriculum to help you learn about the world of artificial intelligence.
In 12 weeks, you will be provided with an Introduction and history of ai, as well as Symbolic ai, Introduction to Neural Networks, Computer Vision, Natural Language Processing, and other ai techniques.
Link: Azure OpenAI Service
You've probably heard a lot about OpenAI in the year 2023. It's time to learn more about it!
With large language models (LLM) becoming more popular; Some of you may be interested in learning more about them. Rapid engineering and generative ai is what the tech world is talking about now, and you can do it too with this course.
Start by learning about rapid engineering and then move on to the fundamentals of responsible generative ai. Put what you've learned into practice with rapid engineering with GitHub Copilot and Azure OpenAI.
If you want to continue learning about Azure OpenAI, you can do so and take your generative ai skills to the next level.
Link: Custom machine learning models
Now that you have a good idea of ai and the Azure ai service, you probably want to get down to business with a lower level: machine learning models. This is where you will understand the true beauty behind ai.
Another learning path that will help you discover tools to build and run your model, with your own data. Being able to improve your machine learning model is a skill in itself.
You'll learn how to build computer vision solutions, process and translate text, extract data from forms, automate machine learning model selection, and deploy and consume models.
Link: Build apps with Azure ai
Want to learn even more about Azure? Let's dig a little deeper with this learning material that includes articles, YouTube videos, and actual module content.
This course will help you learn about the range of tools you can use to build ai-powered applications using Azure ai services. If you're interested in generative ai, you can develop solutions with Azure OpenAI Services, as well as explore chatbots and other ai models in Microsoft Copilot Studio.
Then you will have had the opportunity to learn about ai and its fundamentals, and then put it into practice by creating a custom machine learning model and application. You might be thinking, “How can ai become a part of my daily life?”
This course will address exactly that. Although this content is recommended for developers, it may be the path you want to take.
Optimize your work with GitHub Copilot by starting by learning ai with GitHub Copilot and understanding how they work together.
Just like that, you're one step closer to achieving your 2024 goals with great free resources. Let us know what you liked about the content in the comments section!
nisha arya is a data scientist and freelance technical writer. She is particularly interested in providing professional data science advice or tutorials and theory-based data science insights. She also wants to explore the different ways in which artificial intelligence can benefit the longevity of human life. A great student looking to expand her technological knowledge and writing skills, while she helps guide others.
