Suitable for students in Middle School and High School
This course is ideal for students who want to learn building statistical machine learning algorithms using Python. Anyone who is familiar with python and AI and python basics (or) has taken AI Courses (M2 or M4) and Build a chatbot with AI (PA1) courses is suitable for taking this class. Having taken the Data Science with Python (PA3) course is advantageous, but not a requirement.
Suitable for:
• Those who are familiar with the basics of AI and python and in Grade 8 or higher (OR)
• Those who have taken Build a Chatbot with AI and Python (PA1) and AI Basics (M1).
Learn Artificial Intelligence - a new technology that is shaping our world!
Prerequisite:
Students enrolling are expected to have a basic background in python (data structures, functions, importing modules etc). Any student who has taken an entry level python course with us (PA1 or Summer Camp) automatically qualifies for this course.
Why learn Python?
Python is a language in very high demand because of its versatility and penetration into just about every industry. It can be used for building artificial intelligence systems, web development, graphic design, gaming and the list goes on.
Now is the time for your child to get introduced to the world of coding and python. All our classes are designed around projects that they build incrementally by using concepts learnt in each consecutive class.
Why choose AIClub?
• Designed by AI experts with PhDs in Computer Science!
• These classes are the only ones where students get to build AIs from the very first class, which is precisely why they are so popular among students who love the opportunity to learn about and create these technologies!
We have no math or programming requirement. If they would like to code, they can do that also! Kids get interested and start building fun AI applications and also get motivated to learn programming, math and more STEM topics.
Description
This course introduces students to python packages like scikit-learn and how to use them for training an AI algorithm. The course will cover both Machine Learning and basic Neural Networks (Multi-Layer Perceptrons) and using them directly in Python via scikit-learn.
Topics, Tools, and Modules:
• How scikit-learn can be used to train ML algorithms.
• Tune the hyper-parameters of this algorithm
• How to modify data and tune the algorithm to improve training and prediction performance.
The students will build a custom project in Python and learn how to debug, test and present their final application in a demonstration. With the knowledge gained in this class, students can access public datasets like Kaggle, process the data in python, and do their own programming to continuously retrain the algorithms with new data.
What students take away
• A custom AI project built using Python.
• One year access to an online cloud account where they can continue to build new projects and learn more AI.
• Opportunities to compete and win in AI competitions. For more information on this, visit our Research Program.
• Certificate of Completion
Schedule
Duration: 8 weeks / 1.5 hours per session
We offer a range of dates and times to accommodate busy schedules.
Since we use entirely online tools, if a student must miss a class, it is easy for them to do the required work at home. We provide materials for missed classes and drop in times for students to come in for personal assistance on material covered in a missed class. We do ask however that the student attend the first and last class since this is needed for them to get oriented and also complete their custom project.
Important Notice: The class schedules listed here are fixed. Session rescheduling is not possible in the event of student absence, even if the class has only one student. Thank you for your understanding.