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Course Code: DIGTR 113
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Digital Transformation and Innovation
Course Sector:
Digital Transformation and Innovation
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Introduction
Training course introducion / brief
Artificial intelligence (AI) is increasingly finding its way into industrial and manufacturing contexts. There are even AIs being used to conduct high-frequency trading on the stock market. AIs have a great deal to offer the world of engineering. Some of the most exciting current and prospective uses of artificial intelligence are within the field of engineering. With the rapid evolution of technology, there will be an increased need for engineers to research, create and test AI systems.
This training course is designed to provide participants with the various concepts of Artificial Intelligence like Machine Learning with Python, Deep Learning with TensorFlow, Artificial Neural Networks, Statistics, Data Science, SAS Advanced Analytics, Tableau Business Intelligence, Python and R programming, Build Chatbots with Watson Assistant, and MS Excel through hands-on projects. This course will also provide an overview of future foresight and the concepts that will help participants gain knowledge and skills in futures studies in a visionary and futures-oriented way.
Course Objectives
At the end of the training course, participants will be able to
Course Audience
Who is this course for, and can benefit the most
- Business and technology leaders
- Business Unit Managers
- Business Development Consultants
- General Managers / Regional Managers
- Senior and mid-level leaders
- individual leaders of all levels in the organization
- Art Director
- Marketing Consultants
- Marketing Development Manager
Course Outline
The course aims and learning outcomes
Introduction to Artificial Intelligence domain
- How Data science and Artificial Intelligence overlap
- Importance of Python coding for data analytics
Efficient design of Machine Learning systems
- SAS tool for data analytics, modeling and visualization
- Working with Tableau interactive dashboard and reports
MS Excel calculations, tables and formulae
- R Statistical computing for Data Science
- Building of Artificial Neural Networks and Statistical Models
Deep Learning techniques and working with TensorFlow
- Origins and development of futures thinking
- Role of foresight in today’s world
Key concepts of foresight
- Scenario planning, horizon scanning, megatrends, weak signals and wild cards
- Ethics of foresight
- How to apply foresight methods in our work
Providers and Associations
Providing the best training services and benefits to our valued clients
Boost certificate of completion
BOOST's Professional Attendance Certificate “BPAC” is always given to the delegates after completing the training course, and depends on their attendance of the program at a rate of no less than 80%, besides their active participation and engagement during the program sessions.
ENDORSED EDUCATION PROVIDER
Flexible deadlines
Customized dates accordance to your schedule
Shareable Certificate
Earn certificate upon completion
COURSE METHODOLOGY
Our Training programs are implemented by combining the participants' academic knowledge and practical practice (30% theoretical / 70% practical activities).
At The end of the training program, Participants are involved in practical workshop to show their skills in applying what they were trained for. A detailed report is submitted to each participant and the training department in the organization on the results of the participant's performance and the return on training. Our programs focus on exercises, case studies, and individual and group presentations.
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