Price 2,094 ILS


Course Overview

Machine learning and other AI technologies break software limitations and are especially proficient atsolving problems and providing insights that couldn’t be achieved with conventional technology.Artificial Intelligence will significantly expand the capabilities of technology to go above and beyond their current boundaries, and will allow decision makers to create meaningful competitive advantages and even new product categories. The Innovative Solutions for AI seminar is aimed at managers and decision-makers to allow them an understanding of this technology and its capabilities and to give them the tools to make decisions for competitive advantages. We will review a large number of industries – automotive, retail and marketing, health care, security – that are already using this technology to break free from the boundaries of the past. Specific case studies in retail and market analytics, computer vision, and automotive will be examined. Most importantly, we gain an understanding of the principles and scope of this technology.

Course Outline:

1. Introduction – Dani Livne
In this talk we will review the different domains we have in AI, focusing mainly on machine learning and NLP. We’ll describe a few popular algorithms in machine learning and how we use them in the retail market, CRM and Cyber-security domains.
We will then review the work of a data scientist, from data preparation to data validation, to more advanced topics like model calibration and data science in the cloud.

2. When Technology Meets Reality: The Wide Scope of Machine Learning Applications – Israel Ronn
In recent years, machine learning has moved from research into reality. From automotive to healthcare and from cyber security to marketing. Everywhere we see projects, products and initiatives intent on harnessing this technology and thus overcoming past performance limitations.
The lecture will review the wide scope of target industries together with their associated use cases. Special attention will be given to current market trends and prominent projects.

3. Data science in the Retail market – Dani Livne
We will review the main challenges marketers have in the retail domain and different approaches that can be used to handle them.
We then learn about common pitfalls that we face if our model is not carefully designed.
We finish with an example of a model that achieves high scores when run on a real supermarket chain’s data.

4.  Computer Vision – Yossi Cohen
Computer vision is one of the most highly used machine learning fields. It is used by many industries, such as medical, automotive, robotics, defense and more.  Our  lecture will serve as an introductory review to computer vision, its uses, solutions, methods and relevant markets. It will start with the general picture, then we will go through the various applications which will be followed by a thorough market review.

5. Creating Automotive Intelligence-Machine Learning in Automotive Israel Ronn
With the current technological transition occurring in the automotive industry, machine learning is becoming an enabling technology for the entire market. It starts with customer service, involving remote diagnostics and predictive maintenance, and continues with eco-system industries such as insurance telematics and connected car service. Such specified areas are only the appetizer–the most exciting challenges are in the areas of autonomous vehicles and driving assistance features.
In this lecture we will review the various uses of artificial intelligence technologies in automotive and learn about the current status of their use in the industry. Special focus will be given to main players and also to attractive features. The lecture will include product demonstration clips.