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Simplif.ai

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Hello, and thank you for letting us join you on your machine learning journey, however far along that you may be! It doesn't matter if you don't come from a technical or a mathematical background (though it's okay if you do too!); we are releasing this training to help as many people as possible learn about machine learning and AI. We are very excited to be joining you in this journey 😊

Our Goal: provide practical experience in applied AI

  • Provide a 12-week training with a capstone project
  • Help with scoping, designing, implementing POC of AI project
  • Provide guidance throughout the course
  • Provide high-level ML knowledge and intuition
  • Demystifying ML: from “black box” to real application

Your Goal: learn how to implement & troubleshoot AI solutions in 3 months

  • Finish the course
  • Finish the Capstone project

Meeting schedule

Day of week Course content
Mondays Meeting recap from last week & introduction of topics for current week
Tues-Wed-Thur Reading, coding, assignments (office hours on Wednesdays)
Fridays Meeting Q&A of the topics covered during the week

Helpful links


Notes

  • Take the survey prior start of the course. Don't worry, it's completely anonymous.

8-week course schedule

Week # Week Of Course content Total hours
01 August 22 AI Fundamentals: Get started with artificial intelligence
Modules:
1. Get started with AI on Azure

AI Fundamentals: Explore visual tools for machine learning
Modules:
1. Use automated machine learning in Azure Machine Learning
2. Create a regression model with Azure Machine Learning designer
3. Create a classification model with Azure Machine Learning designer
4. Create a clustering Model with Azure Machine Learning designer (Optional)
4hr 30min
02 August 29 AI Fundamentals: Explore computer vision
Modules:
1. Analyze images with the Computer Vision service
2. Classify images with the Custom Vision service
3. Detect objects in images with the Custom Vision service
4. Detect and analyze faces with the Face service
5. Read text with the Computer Vision service
6. Analyze receipts with the Form Recognizer service
3hr
03 September 05 AI Fundamentals: Explore natural language processing
Modules:
1. Analyze text with the Language service
2. Recognize and synthesize speech
3. Translate text and speech
4. Create a language model with Conversational Language Understanding
5. Build a bot with the Language Service and Azure Bot Service
2hr 40min
04 September 12 Finalize Capstone use-case

Python SDK repo
Main services:
azure-cognitiveservices-language-textanalytics
azure-cognitiveservices-vision-computervision
4hr
05 September 19 Capstone project Unlimited
06 September 26 Capstone project Unlimited
07 September 03 Capstone project Unlimited
08 October 10 Capstone project Unlimited

Additional Course Material

Week # Week Of Readings Videos
01 August 22
02 August 29
03 September 05

Capstone Project

Congratulations on making it through the first eight weeks! Now you’re ready to build a cool project!

We are providing the following guideline for the capstone project.

  • Use Azure Cognitive Services to solve a problem of your choice. It will show how easy it is to build an AI solution using Cognitive Services.
  • You have learned the basic understanding/intuition of machine learning throughout the training and is now ready to build an AI solution. Should be comfortable working with APIs based on your use-case (e.g., Python SKD).

We encourage you to keep in mind the following three rules when approaching the capstone project:

  1. Use Azure Cognitive Services (Language or Vision).
  2. Define your use-case. Your use-case is what you’ll be creating including the dataset you’ll be using (deadline by week 8).
  3. Try to create something unique that hasn’t been done before. We could possibly apply for a patent!

Onboarding on Azure

You will be using the NAIP Azure subscription (DI_NA_DataAI_Workshops_001) to follow the training exercises and create your capstone project. You should have access to the NAIP Azure subscription. If you don’t have access, please reach out one of the Simplif.ai coordinators.

In the NAIP Azure account, you will find a resource group made specially for you to use. Your resource group name will be a combination of:

  • The first letter of your first name followed by your last name.
  • E.g., Tony Stark resource group is tstartk.

You may find your resource group here. Make sure you're using the NAIP subscription.

Goals of the capstone project

  • For the capstone project, your goal is to use what you learned throughout the first 8 weeks to create a unique solution that hasn’t been done before using AI.
  • You have up to week 8 (September 5th) to come up with your use-case.
  • We will hold weekly office hours to answer questions you may have and guide you throughout your project.

Possible steps you may want to consider

  1. Think about a use case or a problem you want to solve. Hopefully, something that hasn’t been done before.
  2. Find/create a dataset that can be used to train an AI system to solve the problem. Check it out some datasets here.
  3. Incorporate Azure Cognitive Services into training/deploying your model.
  4. Reiterate and try to improve your model.

Potential project ideas

  • Create a computer vision system that recognizes your pets.
  • Create a resume parser using NLP.
  • Create a model that recognizes anomalies on images (e.g., X-ray images).
  • Create a music recommendation system.
  • Create an NLP system that understands movie reviews as positive or negative.

Don’t worry if these ideas sound too daunting or difficult. By week 8 (September 5th), you should be able to know at least where to start. Also, we will be providing feedback and mentoring during the Capstone project. However, it is expected that you come up with your own use case.

Here’s some advice. Try to create the simplest model you can by the end of the first week of the capstone project phase and use the following weeks to iterate and improve your model. It’s easy to fall into the trap of trying to create something very complex and forget that a working model is better than no model at all.

Happy learning 😊


Datasets & Kaggle Competitions


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