Date(s) - 04/05/2019
11:00 am - 2:00 pm
What To Expect:
- Mode of Delivery – The classes are held both online and in physical classrooms for Individual and Corporates.
- Audience – We have a global audience that logs in to work hand in hand with our world-class instructors.
- Certification – Available in 47+ Countries Prog360 Certification is accepted globally
- Courses available across – USA, Europe, Africa & Middle East, Asia and Australia
What are the course objectives?
At the end of this course, you will be able to:
- Develop an appreciation for what is involved in learning models from data.
- Understand a wide variety of learning algorithms.
- Understand how to evaluate models generated from data.
- Apply the algorithms to a real-world problem, optimize the models learned and report on the expected accuracy that can be achieved by applying the models.
Based on fundamental knowledge of computer science principles and skills, probability and statistics theory, and the theory and application of linear algebra. This course provides a broad introduction to machine learning and statistical pattern recognition.
This course will be taught over 13 weekends starting on May 4, 2019
- Dates: May 4-5, 11-12, 18-19, 25-26 2019
- June 01-02, 08-09, 15-16, 22-23, 29-30 2019
- July 06-07, 13-14, 20-21, 27-28 2019
- Saturday, Sunday every weekend
- 11am – 02pm PST (US Pacific Standard Time)
Why Is This Program Different:
- The Instructors – Our instructors are industry experts, people who have been there and done that. They not only encourage questioning but also give solutions that are practical and applicable at an enterprise level.
- The Practice – We provide an actual cluster for hands-on practicing. It removes the need to install virtual machines and makes learning easier and fun.
- The Curriculum – Created by industry experts to equip attendees to hit the ground running. Our interactive sessions along with the curated curriculum make starting a project at work or attending an interview or just upscaling your career a cake walk.
What you need for this training?
- A laptop and a stable Inernet connection.
- Introduction in Machine Learning.
- Statistical Foundations.
- Decision Tree learning.
- Artificial Neural Networks.
- Support Vector Machines.
- Bayesian Learning.
- Instance based learning.
- Unsupervised learning.
- Reinforcement Learning.
Who should take this program?
This Machine Learning training course will be suitable for:
- Developers aspiring to be a data scientist or machine learning engineer
- Analytics managers who are leading a team of analysts
- Business analysts who want to understand data science techniques
- Information architects who want to gain expertise in machine learning algorithms
- Analytics professionals who want to work in machine learning or artificial intelligence
- Graduates looking to build a career in data science and machine learning
- Experienced professionals who would like to harness machine learning in their fields to get more insights
For any enquiries you can always reach us at email@example.com.
Corporate Training Solutions also available.