Leveraging AI as a chemist

AI in Chemistry

A course on: Leveraging AI as a Chemist

A Guide to Using AI in Chemistry

Chances are you have seen the recent outputs of ChatGPT and other AI platforms. They are quickly changing the information landscape, transforming work-flows and providing the leverage to 10x individuals outputs. AI in Chemistry has already started changing the field. If you don’t want to be replaced by the new wave you will need to learn to master the technology!

Artificial intelligence (AI) is quickly becoming an essential tool in the field of chemistry, helping researchers and professionals make faster, more accurate predictions and discoveries. In this guide, we will explore some of the ways that AI is currently being used in chemistry, as well as tips on how to get started with using AI in your own research or work.

  1. Identify the problem you want to solve. Before you begin using AI in your chemistry work, it’s important to identify the specific problem or question that you want to address. This will help you determine which type of AI algorithm is best suited for your needs, and will also help you evaluate the results of your analysis.
  2. Choose the right AI algorithm. There are a variety of different AI algorithms that can be used in chemistry, including machine learning, deep learning, and neural networks. Each algorithm has its own strengths and weaknesses, so it’s important to choose the one that best fits your needs.
  3. Gather and pre-process your data. In order to use AI in your chemistry work, you will need to gather and preprocess large amounts of data. This may include collecting experimental data, curating databases, or processing large sets of simulation data.
  4. Train and test your AI model. Once you have your data preprocessed, you can train and test your AI model. This step is critical for evaluating the accuracy and reliability of your AI model, and will help you fine-tune your parameters to achieve optimal results.
  5. Interpret and communicate your results. Once you have trained and tested your AI model, it’s important to interpret and communicate your results to others in your field. This may involve writing a research paper, presenting at a conference, or creating a user-friendly interface for others to interact with your model.
  6. Keep up with the latest developments. AI is a rapidly evolving field, and new developments are constantly being made. To stay up-to-date with the latest developments, it is important to keep an eye on relevant research papers and attend conferences and workshops.

By following these steps, you can begin to explore the many ways that AI can be used in chemistry and make the most of this powerful technology in your own work.

Course Structure

Module 1. Chemically framing the problem

Module 2. Selecting the algorithm

Module 3. Data structures & curation

Module 4. Training the model

Module 5. Interpreting outputs

Module 6. Continued community learning

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Your Instructor

Joshua Mills

Education: Bachelor of advanced science (medicinal chemistry and medical science) from USYD

Course Structure

What would a skill to 10x your current work output be worth to you? Master the skill you need to achieve 10 years of work in 1, master AI in Chemistry.


Module 1. Framing the chemistry problem as an AI problem

Module 2. Selecting the algorithm

Module 3. Data structures & curation

Module 4. Training the model

Module 5. Interpreting AI outputs and communicating it chemically

Module 6. Continued community learning, connect with likeminded chemists

Join the wait list

Priority is given to those who sign-up first

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