Next Generation Decision Making - Pragmatic Artificial Intelligence
Become an AI visionary by using AI techniques in your activities to boost productivity
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. 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.
What you'll learn-and how you can apply it
- 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
This training course is for you because...
You are a Manager, Consultant, or a Developer who wish to enhance their Artificial-Intelligence-driven 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.
Materials, downloads, or Supplemental Content
During the course, you will need to download nothing at all. You can view live programs running available with Artificial Intelligence by Example, professional AI websites, and materials carefully prepared or chosen for the course. ma After the course or during the course, as you wish, you will be able to download programs and documents from GitHub for those who wish to get into the tech aspects.
The material will be available at https://github.com/Denis2054/ The size of the packages will remain small enough to that effect.
About your instructor
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 Prolong 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.
The timeframes are only estimates and may vary according to how the class is progressing
Section 1: Explore the state of art, ground-breaking AI solutions - 50 minutes
- Lecture: 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.
- Lab: Building a basic AI project checklist using an online form you will be able to keep.
Break: 10 mins
Section 2: AI in Robotic Process Automation (RPA) - 50 minutes
- Lecture: 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 generate profit.
- Lab: Deciding which solutions (RPA, AI or AI-RPA) to use for a real-life project using an online form.
Break: 10 mins
Section 3: AI, databases and Big Data - 50 minutes
- Lecture: How and when to integrate artificial intelligence into standard databases (SQL Server, Oracle, MySQL, other) and Big Data solutions. We will explore this critical aspect of any software project through real-life case studies.
- Lab: Deciding which type of database, databases or data source to use on an online form for a real-life project.
Break: 10 mins
Section 4: Case study - 60 minutes
- Lecture: Taking a standard project from the specifications provided to implementation using classical tools and artificial intelligence. 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 KPI and ROI Artificial Intelligence form to prove your point
Section 5: Automated Planning and Scheduling - 50 minutes
Lecture: 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.
Lab: Checking the functionality you would like to use on an online form: which information to run machine learning on and which actions you would like to trigger based on your decision rules. Also which information you would like machine learning to provide to make your own final human decision.
Break: 10 mins
Section 6: Warehouse AI - Optimizing and management - 50 minutes
Lecture: 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.
Lab: Using an online form to decide how this technology could apply to your business or transpose it to other areas beyond warehouse management.
Break: 10 mins
Section 7: AI applied to Key Performance Indicators (AI-KPI) - 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.
Lab: Using an online form to find areas your activity could benefit from preventive decision making to avoid problems before they happen.
Break: 10 mins
Section 8: An advanced case study using all the AI and technologies covered - 60 minutes
Lecture: How all of the technology presented in this course put together can generate exponential productivity and profit. 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.
Lab: Using an online form to check the technology you could use for each department of your activity.
Wrap-up: Summary, Discussions (30 min)
- Interactive Discussion on the basic and ground-breaking aspects of the course