AI-First Engineering Cybertraining

This course introduces the students to AI-First principles. The notes are prepared for the course taught in 2021.

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Class Material

As part of this class, we will be using a variety of sources. To simplify the presentation we provide them in a variety of smaller packaged material including books, lecture notes, slides, presentations and code.

Note: We will regularly update the course material, so please always download the newest version. Some browsers try to be fancy and cache previous page visits. So please make sure to refresh the page.

We will use the following material:

Course Lectures and Management

Course Lectures Course Lectures. These meeting notes are updated weekly (Web)


This course is built around the revolution driven by AI and in particular deep learning that is transforming all activities: industry, research, and lifestyle. It will a similar structure to The Big Data Class and the details of the course will be adapted to the interests of participating students. It can include significant deep learning programming.

All activities – Industry, Research, and Lifestyle – are being transformed by Artificial Intelligence AI and Big Data. AI is currently dominated by deep learning implemented on a global pervasive computing environment - the global AI supercomputer. This course studies the technologies and applications of this transformation.

We review Core Technologies driving these transformations: Digital transformation moving to AI Transformation, Big Data, Cloud Computing, software and data engineering, Edge Computing and Internet of Things, The Network and Telecommunications, Apache Big Data Stack, Logistics and company infrastructure, Augmented and Virtual reality, Deep Learning.

There are new “Industries” over the last 25 years: The Internet, Remote collaboration and Social Media, Search, Cybersecurity, Smart homes and cities, Robotics. However, our focus is Traditional “Industries” Transformed: Computing, Transportation: ride-hailing, drones, electric self-driving autos/trucks, road management, travel, construction Industry, Space, Retail stores and e-commerce, Manufacturing: smart machines, digital twins, Agriculture and Food, Hospitality and Living spaces: buying homes, hotels, “room hailing”, Banking and Financial Technology: Insurance, mortgage, payments, stock market, bitcoin, Health: from DL for pathology to personalized genomics to remote surgery, Surveillance and Monitoring: – Civilian Disaster response; Miltary Command and Control, Energy: Solar wind oil, Science; more data better analyzed; DL as the new applied mathematics, Sports: including Sabermetrics, Entertainment, Gaming including eSports, News, advertising, information creation and dissemination, education, fake news and Politics, Jobs.

We select material from above to match student interests.

Students can take the course in either software-based or report-based mode. The lectures with be offered in video form with a weekly discussion class. Python and Tensorflow will be main software used.

Lectures on Particular Topics

Introduction to AI-Driven Digital Transformation

Introduction to AI-Driven Digital Transformation (Web) Introduction to AI-Driven Digital Transformation (Web)

Introduction to Google Colab

A Gentle Introduction to Google Colab (Web) A Gentle Introduction to Google Colab (Web)
A Gentle Introduction to Python on Google Colab (Web) A Gentle Introduction to Python on Google Colab (Web)
MNIST Classification on Google Colab (Web) MNIST Classification on Google Colab (Web)
MNIST Classification with MLP on Google Colab (Web) MNIST-MLP Classification on Google Colab (Web)
MNIST Classification with RNN on Google Colab (Web) MNIST-RNN Classification on Google Colab (Web)
MNIST Classification with LSTM on Google Colab (Web) MNIST-LSTM Classification on Google Colab (Web)
MNIST Classification with Autoencoder on Google Colab (Web) MNIST-Autoencoder Classification on Google Colab (Web)
MNIST Classification with MLP + LSTM MNIST with MLP+LSTM Classification on Google Colab (Web)
Distributed Training with MNIST Distributed Training with MNIST Classification on Google Colab (Web)
PyTorch with MNIST PyTorch with MNIST Classification on Google Colab (Web)


Health and Medicine

Sports Health and Medicine sector has become a much more needed service than ever. With the uprising of the Covid-19, resource usage, monitoring, research on anti-virals and many more challenging tasks were on the shoulders of scientists. To face such challenges, AI can become a worthy partner in solving some of the related problems efficiently and effectively.

AI in Banking

AI in Banking AI in banking has become a vital component in providing best services to the peopel. AI provides securing bank transactions, providing suggestions and many other services for the clients. And legacy banking systems are also being reinforced with novel AI techniques to migrate business models with technology.

Space and Energy

Space and Energy Energy is a term we find in everyday life. Conserving energy and smart usage is vital in managing energy demands. Here the role played by AI has become significant in recent years. Many efforts have been taken by industry leaders like Bill Gates to provide better solutions for efficient energy consumption. Apart from that Space explorations are also being reinforced with AI. Better communication, remote sensing, data analysis have become key components in succeeding the challenge to unravel the mysteries in the universe.

Mobility (Industry)

Mobility (Industry) Mobility is a key part in everyday life. From the personal car to space exploring rockets, there are many places that can be enhanced by using AI. Autonomous vehicles and sensing features provide safety and efficiency. Many motorcar companies have already moved towards AI to power the vehicles and provide new features for the drivers.

Cloud Computing

Cloud Computing Cloud computing is a major component of Today's service infrastructures. Artificial intelligence, micro-services, storage, virtualization and parallel computing are some of the key aspects of cloud computing.


Commerce Commerce is a field which is reinforced with AI and technologies to provide a better service to the clients. Amazon is one of the leading companies in e-commerce. The recommendation engines play a major role in e-commerce.

Complementary Material

  • When working with books, ePubs typically display better than PDF. For ePub, we recommend using iBooks on macOS and calibre on all other systems.


Piazza Piazza. The link for all those that participate in the IU class to its class Piazza.

Scientific Writing with Markdown

Markdown Scientific Writing with Markdown (ePub) (PDF)

Git Pull Request

Git Pull Request Git Pull Request. Here you will learn how to do a simple git pull request either via the GitHub GUI or the git command line tools

Introduction to Linux

This course does not require you to do much Linux. However, if you do need it, we recommend the following as starting point listed

The most elementary Linux features can be learned in 12 hours. This includes bash, editor, directory structure, managing files. Under Windows, we recommend using gitbash, a terminal with all the commands built-in that you would need for elementary work.

Linux Introduction to Linux (ePub) (PDF)

Older Course Material

Older versions of the material are available at

Lecture Notes 2020 Lecture Notes 2020 (ePub) (PDF)
Big Data Applications (Nov. 2019) Big Data Applications (Nov. 2019) (ePub) (PDF)
Big Data Applications (2018) Big Data Applications (2018) (ePub) (PDF)


You can contribute to the material with useful links and sections that you find. Just make sure that you do not plagiarize when making contributions. Please review our guide on plagiarism.

Computer Needs

This course does not require a sophisticated computer. Most of the things can be done remotely. Even a Raspberry Pi with 4 or 8GB could be used as a terminal to log into remote computers. This will cost you between $50 - $100 dependent on which version and equipment. However, we will not teach you how to use or set up a Pi or another computer in this class. This is for you to do and find out.

In case you need to buy a new computer for school, make sure the computer is upgradable to 16GB of main memory. We do no longer recommend using HDD’s but use SSDs. Buy the fast ones, as not every SSD is the same. Samsung is offering some under the EVO Pro branding. Get as much memory as you can effort. Also, make sure you back up your work regularly. Either in online storage such as Google, or an external drive.

Project Guidelines

We present here the AI First Engineering project guidelines

Last modified June 16, 2021 : merge content (ecf6e8f7)