Training Content
Training Duration: 5 Days, each day 09:00–12:00 Theory, 13:00–16:00 Practice
Level: Introductory (preparation for all technical fields)
Participant Profile
• Those who will attend technical trainings such as Robotics, Artificial Intelligence, Image Processing, Cybersecurity
• Those lacking basic math/statistics knowledge in programming and engineering courses
• Pre-university / university students and industry employees
• Professionals interested in general technical fields
• Direct preparatory training for participants planning to continue into advanced technical programs (AI, Robotics, Image Processing, Cybersecurity, etc.)
Prerequisites / Requirements
• Basic computer knowledge
• High school–level knowledge in mathematics and science is recommended (if participants have limited background, the instructor simplifies explanations)
• Participants may be directed to advanced technical trainings after completing this course
Curriculum
Day 1: Basic Mathematics
• Numbers, functions, equations
• Logarithms, exponential functions
• Introduction to vectors and matrices
• Practice: small calculation and problem-solving exercises
Day 2: Linear Algebra & Geometry
• Matrix operations, determinant, inverse matrix
• Solving linear systems
• 2D / 3D coordinates, transformations
• Practice: matrix operations, simple transformations
Day 3: Basic Statistics
• Mean, median, variance, standard deviation
• Fundamentals of probability, distributions (Normal, Binomial, Poisson)
• Reading and interpreting data
• Practice: statistical calculations with small datasets
Day 4: Fundamentals of Physics
• Force, motion, speed, acceleration (Newton’s laws of motion)
• Energy, work, power
• Electricity: current, voltage, resistance
• Practice: basic experimental calculations and problem solving
Day 5: Applied Studies & Mini Project
• Examples of mathematical modeling (e.g., simple robot motion)
• Data analysis activity (statistical evaluation)
• Solving a physical scenario (e.g., drone flight dynamics)
• Group work and presentation
Learning Outcomes
• Gains mathematical calculation and modeling skills
• Can perform statistical thinking and data analysis
• Can interpret physical phenomena (force, motion, energy) at a basic level
• Develops scientific thinking and problem-solving abilities
• Becomes prepared for subsequent advanced technical trainings
Training Notes
• The instructor may deepen or simplify topics depending on participant level
• This course serves as a mandatory preparatory stage for those planning to attend advanced technical trainings (AI, Robotics, Image Processing, etc.)
• Participants receive a university or institution–approved certificate upon completion