Data Science and Machine Learning Practical tools and programing & Innovative Applications for AI
Package including 2 courses :
- Data Science and Machine Learning Practical tools and programing
- Innovative Applications for AI
Référence de la formation
Nombre de jours
6 days, 4H/day
2.010,15 € HT
Lieu de la formation
V: v-learning, virtual class
Basic programming skills in C, Java or any other language
- High level Managers, Presale Managers, IT Managers, QA and Technical Support or those who would like to understand the different problems that are suitable for machine learning and exercise different frameworks.
- Project Managers, Product people and Managers, Developers and Architects who wants to know about AI.
Objectifs de la formation
Data scientists use a set of algorithms which enables computers to solve problems that are classified on a higher complexity level than traditional algorithms. Examples of such cases are
Machine learning algorithms allow the computer to train and learn from its own mistakes and thus perfect its performance on new data. This course gives the basis of understanding the data scientist environment, focusing mainly on common frameworks in order to enable selecting the appropriate approach to the problems at hands.
Machine learning and other AI technologies break software limitations and are especially proficient at solving 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 many 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.
Contenu du cours
#Course-1 : Data Science and Machine Learning Practical tools and programing
|Introduction to data science||
• Examples and use cases
• Statistics 101
• Machine learning introduction
|Data preparation using various tools||
• Exploratory data analysis
• Cleaning the data
• Filtering and scaling
• Outliers and null values
|Running machine learning algorithms||
• Regression and decision trees
• Statistical reasoning
• Weka Introduction
Mini project Part A:
• Data Preparation
• Feature selection
|Machine learning in cloud environment, Big Data||
• Association Rules
• Decision Trees
|Validation of Results||
• Standard metrics
• ROC curve analysis
Mini Project Part B:
• Estimation of different models
|• Summary including Q&A|
#Course-2 : Innovative Applications for AI
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.
The Wide Scope
of Machine Learning
In recent years, machine learning has movedfrom research into reality. From automotive to
Data science in the Retail
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.
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.
Learning in Automotive
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.
13 Juillet 2020 au 22 Juillet 2020
17 Août 2020 au 19 Août 2020
Package including 2courses, we offer 10% off including in the price