This is a course for live online AI sessions.

Provide insight on how to implement real-life AI solutions in a holistic way using all of the tools available to us.

The courses are an extension of Artificial Intelligence by Example by Denis Rothman:

Obtain the book on Packt

Obtain the book on Amazon

The program(s) for this course are Google Jupyter Python-Tensorflow Notebooks. You have nothing to install!
Guide to use Google Jupyter Notebooks for this course

The programs are under the MIT License. THe programs are for educational purposes only. Thus do not use them before checking Google, Facebook and Twitter security policies. Also be sure to follow web and General Data Protection Regulations (GDPR). Take your time and explore each policy rule. It is a major part of a project. The more you respect privacy and security policies, the more your users and customers will trust you!

When creating Twitter, Facebook, for example, you will need to provide your terms of service and privacy policy. If you do not have one, there are plenty of examples online. Start by googling "terms of service form and privacy policy examples" or similar search keywords.

Outline of the course This course provides a comprehensive view of how artificial intelligence can provide decision-making tools for a wide range of problems to solve. The course shows how AI can analyze, predict and anticipate problems providing preventive decision making in real-time.

You will explore how to apply artificial intelligence to specific profit-generating areas in your company and use cutting-edge machine learning performance measurements to make real-time decisions.

This course covers the key aspects of artificial intelligence from the tools to their implementation on local servers or cloud platforms. We will take a project-based approach to understand how future AI solutions are built and the best use cases for deploying them. Once implemented, we will discover how to use these AI tools for predictive and preventive decision-making.

We will start by exploring the building blocks of artificial intelligence through programs and videos that will be run live. At that point, you will have fully understood the tools involved and will see how to maximize your company or personal projects.

One of the leitmotivs of the course will be to introduce you to chaos engineering techniques first introduced by Netflix and recommended for all businesses. We will use proven AI Automated Planning Management algorithms to apply chaos engineering to predict unforeseen events classical techniques cannot detect.

We will see how artificial intelligence enhances optimizing profit by interacting with big data, AI automated planning and AI supply chain management tools(SCM). At each step, you will discover how to implement a solution now in a very pragmatic way based on real-life case studies.

Finally, we move to manage a project involving standard software (CRM, ERP, SCM) and the full range of artificial intelligence tools and extensions. We will optimize an entire supply chain from e-commerce to delivery exploring service production, product production, storage, and delivery constraints. We will see how to motivate your workforce and automatically detect slight perturbations in your strategic plans to avoid major problems.

By the end of this course, you will be confident enough to manage an artificial intelligence project from scratch to successful implementation for your users using local servers, cloud platforms such as Amazon Web Services, Google Cloud, Microsoft Azure, and IBM Cloud. You will master the power of chaos management machine learning algorithms that will provide predictions and automated problem-solving solutions.

Modern day management requires to have a strategic vision. That vision is challenged on a daily basis of unforeseen problems that require unplanned energy and resources. This course will show how to use the power of pragmatic artificial intelligence KPI (Key Performance Indicators) that contain predictive and preventive decision-making information. You will discover the cutting edge methods of machine learning chaos management.

This training is aimed at teaching you how to implement pragmatic quick win profit generating artificial intelligence projects on a local or cloud platform. You will explore the innovating combination of state of art artificial intelligence tools and innovative real-time AI management methods..

● Building an artificial intelligence project that is fully integrated into corporate environments: databases, CRM, ERP and other systems such as MES and IoT.
● Deploy cross-platform AI solutions along with services including machine learning functions on local and cloud servers
● Master predictive and preventive decision-making with cutting-edge machine learning algorithms
● Enable your data scientists to tap into the huge money-making possibilities of your data
● Enable consultants to use cloud solutions without requiring corporate expertise to implement artificial intelligence solutions
● Make your team proud to be part of the future and increase their productivity
● Become a well-known leader in implementing artificial intelligence and enhance your professional or personal brand image

The course is aimed at managers, consultants, developers/IT Operations who wish to enhance their artificial intelligence management skills and culture. If you have had a hard time finding how to use artificial intelligence in a pragmatic realistic way, here is your one-stop opportunity!

Artificial Intelligence by Example

It would be a good idea to go through the book before the course. No need to understand the programs but focus on the real-life case studies in the book. They are all based on real-life projects (names and confidential technology changed) that generated profit for major corporations.

No developing experience is required.

Note: Developers that are present will learn how to manage projects and fully understand the constraints of project management.

The principal preparation is for you to think of how you would like to use artificial intelligence in your company. What aspect of your company would you like to optimize? Where is the productivity lagging? Which area in your company would predictive and preventive decision making be useful? Which decisions would like to automate and which would you like to make on your own with AI KPIs (Key Performance Indicators)?
Write down a few basic questions and answers you would like to start building your project with.
You will be implementing this during the live training on your website (you can turn it on and off during testing). Then you will be learning how to deploy it on several key platforms.
You will be learning how to implement your project during the live training. You will fully understand how to deploy artificial intelligence in your company using ground-breaking technology.
You will be able to apply what you learned right after the course through a pragmatic step by step method.

During the course, you will need to download nothing at all.
The material will be available and you will be able to view everything online at https://github.com/Denis2054/NEXTGENAI
The readme file and all the material will be available 48 hours before the beginning of the course.
We will be using Jupyter notebooks online. There is nothing to install.
You will just need a Google account and a Google Drive Account which comes free with a Google account.
After the course or during course, and only for those who wish, you will be able to download programs and documents from GitHub to read and run them on your machine(s).

The timeframes are only estimates and may vary according to how the class is progressing

(Instructor Lecture, lab, Q&A) - 50 minutes

Viewing and understanding artificial intelligence, machine learning, and deep learning algorithms. Learning how they work and how to use them in a practical real-life project.

Building a basic AI project simulation checklist using the online course form you will be able to keep. Each workshop will add more elements to this document.

(Instructor Lecture, lab, Q&A)- 50 minutes

Learning how to first try to use RPA without artificial intelligence to build a solid database and process environment. Then introduce a specific artificial intelligence algorithm in the system to control all of the parameters of a multi-agent system with an advanced predictive decision-making algorithm.

Deciding which solutions (RPA, AI or AI-RPA) to use for a real-life project using the online document started in section 1.

(Instructor Lecture, lab, Q&A), - 50 minutes

How and when to integrate artificial intelligence into standard databases (SQL Server, Oracle, MySQL, other) and Big Data solutions. Using machine learning to analyze the quality of the data provided, extract the accurate data and produce lists of noise in the data (errors, inaccurate information).
We will explore this critical aspect of any software project through real-life case studies.

Deciding which type of database, databases or data source to use in the online course document for a real-life project.

(Instructor Lecture, lab, Q&A) - 60 minutes

How to convince a team to use an AI solution through a POC(Proof of Concept) approach including KPIs(Key Performance Indicators) and ROI( Return on Investment). Lab: Building a AI-KPI and ROI system on the online course document to prove your point

(Instructor Lecture, lab, Q&A) - 50 minutes

How it has become impossible to make accurate decisions with the amount and variety of data that is now available. The information input changes so quickly it has become a challenge to adapt and replan a strategy. Automated Planning and Scheduling using Machine Learning algorithms can parse all the data available, distinguish reliable from unreliable data, key indicators and valuable decision making information. We will explore real-life AI case studies for data centers, services, and manufacturing. We will explore how to manage hundreds of parameters through machine learning and detect slight variances from the initial goals. Then we will see how automated preventive methods will solve a problem in real-time before it goes out of control.

which information to run machine learning on which actions you would like to trigger based on your decision rules. which information you would like machine learning to provide to make your own final human decision.

(Instructor Lecture, lab, Q&A) - 50 minutes

The rise of e-commerce has generated huge warehouses and thousands of decisions to make daily: optimal warehouse locations, the best storage areas, the cost-effective pier organization, transport cost management and all the aspects of SCM (Supply Chain Management). Artificial Intelligence provides the tools to run decision-making algorithms and provide effortless actions and reports for managers to use in real-time. We explore real-life AI case studies for several types of warehouses and supply chain models. We will also see how to apply these models to other domains through transfer learning.

Using the online course document to decide how this technology could apply to your business or transpose it to other areas beyond warehouse management.

(Instructor Lecture, lab, Q&A) - 50 minutes ###Lecture We will discover how artificial intelligence can identify a slight change in a strategic plan of a corporation, predict a negative variance to come (future production and deliveries) and provide powerful KPIs (Key Performance Indicators) that enable a manager to anticipate problems and solve them before they actually occur. We will explore real-life case studies and see how AI can predict a future problem, anticipate the actions to be taken and provide a clear vision to a manager.

Using the online course document to find areas your activity could benefit from preventive decision making to avoid problems before they happen.

Break: 10 mins

(Instructor Lecture, Lab, Q&A) - 60 minutes

We will explore how this technology applies to e-commerce, sales in general, human resource management, production, warehouse, and delivery management.

We will discover the efficiency of a multi-agent system over a single central program. Predictive machine learning tools will show how to automate plan changes in real-time.

Interactive Discussion on the basic and ground-breaking aspects of the course

Denis Rothman graduated from l'Université Paris-Sorbonne and l'Université Paris-Diderot, writing one of the very first word2matrix embedding solutions.
He began his career authoring one of the first AI cognitive Chatbot 30+ years ago applied to a cognitive & digitized language teaching Chatbot. He customized it for Moët et Chandon (LVMH) and scores of companies in various forms. https://www.linkedin.com/pulse/did-you-miss-ai-parsing-train-denis-rothman He has authored a profit orientated AI resource optimizing system written in Horn Clauses in Prolog for IBM and implemented in corporate environments. He also transposed it in C++, Java and presently in Python/Tensorflow. In the years after, he authored an AI APS (Advanced Planning and Scheduling) solution based on cognitive patterns. This #AI software is used worldwide to this day in the aerospace, train, energy, apparel and many other corporate fields.

Name: Denis Rothman
Personal Websites, blogs and Social network pages:
Artificiel Intelligence Blog
Amazon page
AI website

GitHub

To contact me, the best place is here:
LinkedIn