Kaggle Machine Learning Competition Boot Camp Series

Kaggle is one of the most popular and novice friendly platforms for machine learning competitions, with a wide range of challenges covering topics such as computer vision, natural language processing, and time series analysis.

Step by Step Method to Master AI

Step 1: AI Foundation Course

Step 2: Further Mathematics Course for AI

Step 3: Advanced Python Course with Further Math for AI

Step 4: Neural Network and Deep Learning Course

Further Mathematics Course for Machine Learning/AI

Entry Requirement: Must meet GCSE Math Standard or Equivalent

Prerequisite Course: N/A

Date: Oct 28th - Nov 1st 2024 - 5 Days

Time: Available in Booking Page

School Year Group: Year 8 - Year 13

Tutor-Child Ratio: 1:5; Max 5 Children Per Teacher.

Course Mode: Online

Fee: £250

* Taught by UK Russell Group University Professor

* Course Content designed by UK Russell Group University Professors, Open Source AI Library Author and senior software developers with rich AI Industry experience .

* Study Further Math tailored for A Level, foundational to AI.

* Build the Math foundation for using Python in Machine Learning

* Prerequisite course for our Advanced Python Course with Further Math for Machine Learning/AI course

Enquiry

Course Demo Video

Our approach to Learn Further Math

Consolidate Further Math with AI user cases

Our Coding Platform

Coding Platform with AI Tutor

Day 1 - Linear Algebra:
- Vectors
- Matrices
- Visualization

Day 2 - Linear Algebra:
- Systems of Linear Equations
- Visualization

Day 3 - Calculus :
- Derivatives
- Visualization

Day 4 - Linear Algebra + Calculus:
- Linear Optimization
- Non-Linear Optimization
- Visualization

Day 5 - Calculus:
- Integral Calculus
- Visualization
- Summary of the Further Mathematics in AI

Course Structure

Course Objectives

Essential Mathematical Principles:
- Introduce core mathematical concepts and their applications in AI, covering calculus and linear algebra.

Enhance Logical Thinking:
- Foster problem-solving skills and logical reasoning by exploring mathematical operations and their significance in AI, with focused tasks on vector and matrix operations, solving systems of equations, and optimization techniques.

Prepare for Advanced Studies:
- Lay a strong foundation for future learning in advanced mathematical topics and AI concepts by tackling challenging exercises in calculus, optimization, ensuring a smooth transition to more complex studies.

Encourage Creativity:
- Encourage students to express their creativity and innovation through personalized projects that apply mathematical concepts in AI, such as algorithms in model fitting , gradient descent optimization, and integral calculus applications.

Practice and Review:
- Provide opportunities for practice with targeted exercises and review sessions to reinforce learning, analyze key concepts, and solve problems, ensuring a deep understanding of the mathematical principles essential for AI.

Instructor-Led Sessions:
- The instructor and assistant teacher introduce the basic concepts of each topic, providing full and detailed explanations on calculus and linear algebra with a focus on their significance in AI.

Interactive Exercises:
- Students engage in targeted exercises to apply and practice what they have learned.

Daily Homework Assignments:
- Homework is assigned each day to help students consolidate their understanding of the concepts covered in class.