Courses tagged with "How to Succeed" (8)
This is an introduction to predicate logic and how it is applied in computer science, electronic engineering, linguistics, mathematics and philosophy. Building on your knowledge of propositional logic, you will learn predicate logic—its language, interpretations and proofs, and apply it to solve problems in a wide range of disciplines.
Course Summary
Modelling and simulation make a particular part of the world easier to define, visualize and understand. Both require the identification of relevant aspects of a situation in the real world and then the use of different types of models for different objectives and the definition of the most suitable model parameters.
This course provides to you a number of methods suitable for modelling technical systems and processes in a wide range of applications. These applications cover a range from image processing via machine learning to face recognition.
After introducing the techniques in general, you train their application to real problems employing the widely used modelling and simulation tool MATLAB®.
What will I learn?
- You will be acquainted with the concepts of modelling and simulation
- You will be able to implement and simulate models using MATLAB®.
- You will acquire further knowledge of Image Processing, Optical Character Recognition, Machine Learning and Face Recognition.
- If you are an enthusiastic student with only rudimentary programming knowledge you can acquire an understanding of basic MATLAB® programming.
What do I have to know?
The course will be taught on an academic level for undergraduate students. Therefore, mathematics and physics knowledge of at least secondary education level as well as programming knowledge is a prerequisite. MATLAB® is commercial software. As a result of support from MathWorks, students will be granted a downloadable license to MATLAB® for the duration of the course.
Course Schedule
Chapter 1: Introduction to MATLAB Concepts
Chapter 2: Modelling and Simulation
Chapter 3: The Basic Problem Solving Toolbox
Chapter 4: Advanced Problem Solving Methods
Chapter 5: Statistics and Image Processing
Chapter 6: Machine Learning in a Nutshell
Chapter 7: Optical Character Recognition
Cahpter 8: Face Recognition
2.01x introduces principles of structural analysis and strength of materials in applications to three essential types of load-bearing elements: bars in axial loading, axisymmetric shafts in torsion, and symmetric beams in bending.
The course covers fundamental concepts of continuum mechanics, including internal resultants, displacement fields, stress, and strain.
While emphasizing analytical techniques, the course also provides an introduction to computing environments (MATLAB) and numerical methods (Finite Elements: Akselos)
This course is based on the first subject in solid mechanics for MIT Mechanical Engineering students. Join them and learn how to predict linear elastic behavior, and prevent structural failure, by relying on the notions of equilibrium, geometric compatibility, and constitutive material response.
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