Machine Learning Courses - after school
Academic Year - 2020-21
An exciting opportunity offered by
Machine Learning 1 (Term 2)
Machine Learning 2 (Term 3)
Machine Learning 3 (Summer)
Are You Ready To Reboot Your Life?
Today, Artificial Intelligence, Analytics and Machine Learning are among the biggest drivers of change in the world. These technologies, collectively referred to as Data Science, enable self-driving cars, translate English to Czech, suggest the song you should listen to next, and caption movies to name a few areas in our daily lives.
At RAK Academy, we offer After School Courses to teach our students how Artificial Intelligence is used to solve real world problems and how to build AI so that students are ready for the challenges of the new world as they move in their careers and lives. The curriculum consists of three Machine Learning (ML) courses: ML-1, ML-2, and ML-3. ML-1 starts with basic concepts in Machine Learning and implementation using Python programming language. In ML-2, students learn key Machine Learning methods including Linear Regression and K-Nearest Neighbor. In ML-3, students learn Artificial Neural Network (also called Deep Learning). They learn Mathematics behind these techniques and also learn how to implement these networks using Python Programming language to solve real-life problems. Over last two years over 50 students have graduated from these programs. Many of them decided to pursue education and career in this area.
Prerequisites and Application Process:
The deadline for applying for the Machine Learning - 1 (ML-1) course is 12th January 2021 @ 11:59 pm. The course requires good skills and understanding in Python programming language (to the level of Grade 8 in RAK Academy). This includes being comfortable with nested loops, nested conditions, dictionaries, list comprehension, and use of external libraries. You should also be comfortable with Jupyter Notebook programming environment. You can apply if you are a student of Grades, 9, 10, 11, or 12 at RAK Academy. If you are in Grades 7 or 8, you can still apply if you feel you have good enough knowledge of Python to the level required. You also need to be comfortable with Mathematics. The main characteristic, however, is a zeal to learn and excel. Selection will be based upon submission of an application and a personal statement.
Location and Logistics:
The course ML-1 will be held online 90 minutes twice a week (Mondays and Wednesdays starting 18th January @ 5 PM) through Term 2. Only 20 seats are available in this course (ML-1). This is an intensive course and requires your focus and attention in the sessions and will also include assignments that require additional time. An ML-1 certificate of completion will be provided to those that attend all sessions, complete the assignments, and pass course assessment. The graduates will also be eligible to apply for ML-2 in Term 3.
Why Machine Learning Courses?
You want to jump start your career journey in this most fascinating and high-demand area and want to get a feel of what it takes to become an AI Engineer / Data Scientist.
you are fascinated by how Artificial Intelligence and related technologies have been making inroads in our lives and want to explore this area more.
you have a keen interest in technology and in Computer Science and are trying to explore AI as a career option.
You know that the future belongs to modern technology and much of what professionals do will be driven by or at least related with technology. You want to explore the domain to improve your digital skills to be ready.
These bootcamps will be taught by Dr. Rashed Iqbal, who works as Chief Data and Technology Officer at the Investment and Development Office, an investment fund of Ras al Khaimah Government. Earlier, he worked for Teledyne Technologies, Inc., Western Digital Corporation, Synopsys, Inc., and others in the U.S. in technology and management roles for 20 years mostly in California. He also started and completed multiple entrepreneurial ventures. His latest venture was Narrative Economics in the domain of Text and Emotion Analytics.
Dr. Iqbal also taught graduate courses in Artificial Intelligence, Machine Learning and Data Science at UCLA. He also taught at UC Irvine, and at UCLA Extension. His areas of interest include Text Analytics, Natural Language Understanding, and Lean and Agile Development. He holds a Ph.D. in Systems Engineering from the University of Sheffield, UK.