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ai-expert-roadmap's Introduction

Developer Roadmap

i.am.ai
AI Expert Roadmap

Roadmap to becoming an Artificial Intelligence Expert in 2022

AMAI GmbH MIT License


Below you find a set of charts demonstrating the paths that you can take and the technologies that you would want to adopt in order to become a data scientist, machine learning or an AI expert. We made these charts for our new employees to make them AI Experts but we wanted to share them here to help the community.

If you are interested to become an AI EXPERT at AMAI in Germany, or you want to hire an AI Expert, please say [email protected].

Note

👉 An interactive version with links to follow about each bullet of the list can be found at i.am.ai/roadmap 👈

To receive updates star ⭐ and watch 👀 the GitHub Repo to get notified, when we add new content to stay on the top of the most recent research.

Follow our AI Newsletter to stay up to date with the latest developments in AI. We cover new use cases and research topics.

Disclaimer

The purpose of these roadmaps is to give you an idea about the landscape and to guide you if you are confused about what to learn next and not to encourage you to pick what is hip and trendy. You should grow some understanding of why one tool would be better suited for some cases than the other and remember hip and trendy never means best suited for the job.

Introduction

Fundamentals

Data Science Roadmap

Machine Learning Roadmap

Deep Learning Roadmap

Data Engineer Roadmap

Big Data Engineer Roadmap

🚦 Wrap Up

If you think any of the roadmaps can be improved, please do open a PR with any updates and submit any issues. Also, we will continue to improve this, so you might want to watch/star this repository to revisit.

🙌 Contribution

Have a look at the contribution docs for how to update any of the roadmaps

  • Open pull request with improvements
  • Discuss ideas in issues
  • Spread the word
  • Reach out with any feedback

Supported By

AMAI GmbH AMAI GmbH

ai-expert-roadmap's People

Contributors

aakash-2904 avatar etbox avatar indrajeetdevale avatar jamesmilliman avatar joaojgabriel avatar jstumpp avatar leonard-plotkin avatar rlirli avatar spekulatius avatar

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ai-expert-roadmap's Issues

Misleading map

Thank you for piecing this all together. However, the roadmap is misleading in that there is a strict ordering of [data scientist -> machine learning scientist -> deep learning researcher]. This is misleading as it implies that data scientists are somehow of lower seniority in skills and experience than machine learning scientists and deep learning researchers. When really data scientist, ML scientist, and DL researchers share similar skills as well as having their very own unique skills that other roles might not have. For example, data scientists might be more business-oriented, ML/applied scientists might work closely on applied research/engineering to make sure the developed ML models go into production, and DL researchers might work more on the pure research side. In no way is one job on higher seniority than the other in terms of skills, years of experience, and even education level (although DL researchers typically have PhD more often than ML scientists and data scientists).

Recommendation Books

Hello! They could recommend some books that see the theoretical part. For now, I would be interested in knowing something related to the part of ¨Data Scientist (Statistics and visualitation)¨ and ¨Fundamentals (Exploratory Data Analysis /
Data Munging / - Wranglin)¨. Thanks in advance!

leadpop

the leadpop application that a website in your mobile

Hello

Tyro at github
So creating an issue for learning purpose

AI doubt

Hi,

I am trying to apply AI and ML algorithms in my data, there are hundred thousand stores with competitors, where gas prices changes 15 minutes once.
Assume in each city if I have my own gas station and how should I give my prices so that more customers come to my store.

Can we apply AI for my above logic

Thanks

Bootstrapping

Why isn’t bootstrapping included in confidence intervals? It is a very useful and popular tool.

Intelligent Agents

We should develop agents that deliver goods for the Covid-19 patients in India since we are suffering!

Change the order of the EDA/Data wrangling section and add a few missing things to other parts

Hi all, this is a very nice chart but I believe that there should be slight modifications.

Data Science Roadmap

"Dimensionality and Numerosity Reduction" is a large topic which would include the study of the "Principal Component Analysis" (PCA) algorithm as the very first thing you'd do. Yet PCA is seen as being the very final thing you look at in this section. I think you should put PCA right before Dimensionality Reduction or you should combine them.

In the "Visualization section" you list some nice plotting libraries, but I think that Bokeh should be included here because it is a superior python plotting library (out of the box GPU/OpenGL support allowing for plotting millions of points, significantly more flexible interaction system) combined to the other options and is quickly becoming one of the important graphing libraries.

Under "Data Sources" you may want to put "Data Mining and Web Scraping" or something along those lines since I think a Data Scientist should be able to get their own data rather than go on Kaggle or github awesome pages.

Machine Learning Roadmap

Subsections under "Association Rule Learning" should be "Apriori algorithm", "ECLAT algorithm" and "Fp-trees"

Subsections under Dimensionality Reduction should include (after PCA): "Random Projection", "NMF", "T-SNE", "UMAP"

Subsections under Clustering should include (after Agglomerative): "OPTICS" and "HDBSCAN"

Subsections under "Classification" should include "Guassian Mixture Models"

Logistic Regression is actually a binary classification algorithm, despite its name, so move it from regression to Classification

Moving Huggingface Transformers out from here and into the Deep Learning section.

Deep Learning Roadmap

Add a new section under "Architectures" called "Attention Mechanisms/Transformers"
Add a new section under Architectures called "NEAT/Evolving Architectures"

Big Data Engineer

Add a new blue section under "Tools" for Dask, Numba, Onnx, and OpenVino

If it's really easy to generate these plots, I'm willing to make these changes and submit a PR. What are your thoughts on implementing some or all of these changes?

Add website to description

Consider adding the website url https://i.am.ai/roadmap/ to repo description, that would save lazy people some energy. :)

You should create a course that teaches all this!

This is amazing. Thank you so much for creating it, and for presenting it in an easy-to-read format. It would be really cool if you guys put together an entire course, with videos and everything, teaching all these concepts. Just a suggestion. Thank you again!

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