6.00 Intro to CS and Programming has been retired from OCW. You can access the archived course on DSpace – MIT’s digital repository. Please see the list of introductory programming courses and other programming courses from recent years.

6.00SC Intro to CS and Programming has been retired from OCW. You can access the archived course on DSpace – MIT’s digital repository. Please see the list of introductory programming courses and other programming courses from recent years.

6.0001 Introduction to Computer Science and Programming in Python is intended for students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems and to help students, regardless of their major, feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class uses the Python 3.5 programming language.

This course presents the fundamentals of object-oriented software design and development, computational methods and sensing for engineering, and scientific and managerial applications. It cover topics, including design of classes, inheritance, graphical user interfaces, numerical methods, streams, threads, sensors, and data structures. Students use Java programming language to complete weekly software assignments.
How is 1.00 different from other intro programming courses offered at MIT?
1.00 is a first course in programming. It assumes no prior experience, and it focuses on the use of computation to solve problems in engineering, science and management. The audience for 1.00 is non-computer science majors. 1.00 does not focus on writing compilers or parsers or computing tools where the computer is the system; it focuses on engineering problems where the computer is part of the system, or is used to model a physical or logical system.
1.00 teaches the Java programming language, and it focuses on the design and development of object-oriented software for technical problems. 1.00 is taught in an active learning style. Lecture segments alternating with laboratory exercises are used in every class to allow students to put concepts into practice immediately; this teaching style generates questions and feedback, and allows the teaching staff and students to interact when concepts are first introduced to ensure that core ideas are understood. Like many MIT classes, 1.00 has weekly assignments, which are programs based on actual engineering, science or management applications. The weekly assignments build on the class material from the previous week, and require students to put the concepts taught in the small in-class labs into a larger program that uses multiple elements of Java together.

This course aims to give students the tools and training to recognize convex optimization problems that arise in scientific and engineering applications, presenting the basic theory, and concentrating on modeling aspects and results that are useful in applications. Topics include convex sets, convex functions, optimization problems, least-squares, linear and quadratic programs, semidefinite programming, optimality conditions, and duality theory. Applications to signal processing, control, machine learning, finance, digital and analog circuit design, computational geometry, statistics, and mechanical engineering are presented. Students complete hands-on exercises using high-level numerical software.
Acknowledgements
The course materials were developed jointly by Prof. Stephen Boyd (Stanford), who was a visiting professor at MIT when this course was taught, and Prof. Lieven Vanderberghe (UCLA).

Imagine that you are a bank and a main part of your daily business is to lend money. Unfortunately, lending money is a risky business – there is no 100% guarantee that you will get all your money back. If the borrower defaults, you will face losses in your portfolio. Or, in a bit less extreme scenario, if the credit quality of your counterparty deteriorates according to some rating system, the loan will become more risky. These are typical situations in which credit risk manifests itself.

According to the Basel Accord, a global regulation framework for financial institutions, credit risk is one of the three fundamental risks a bank or any other regulated financial institution has to face when operating in the markets (the two other risks being market risk and operational risk). As the 2008 financial crisis has shown us, a correct understanding of credit risk and the ability to manage it are fundamental in today’s world.

This course offers you an introduction to credit risk modelling and hedging. We will approach credit risk from the point of view of banks, but most of the tools and models we will overview can be beneficial at the corporate level as well.

At the end of the course, you will be able to understand and correctly use the basic tools of credit risk management, both from a theoretical and, most of all, a practical point of view. This will be a quite unconventional course. For each methodology, we will analyse its strengths as well as its weaknesses. We will do this in a rigorous way, but also with fun: there is no need to be boring.

This is MIT's introductory course on deep learning methods with applications to computer vision, natural language processing, biology, and more! Students will gain foundational knowledge of deep learning algorithms and get practical experience in building neural networks in TensorFlow. Course concludes with a project proposal competition with feedback from staff and panel of industry sponsors. Prerequisites assume calculus (i.e. taking derivatives) and linear algebra (i.e. matrix multiplication), and we'll try to explain everything else along the way! Experience in Python is helpful but not necessary.

This course will introduce students to architectural design and computation through the use of computer modeling, rendering and digital fabrication. The course focuses on teaching architectural design with CAD drawing, 3-D modeling, rendering and rapid prototyping. Students will be required to build computer models that will lead to a full package of architectural explorations with computers. Each semester we will explore the design process of a particular building type and building material.
The course also investigates a few design processes of selected architects. The course is critical of design principles and building production methods. Student assignments are graded based on the quality of design, representation and constructability. Great design input is always encouraged.

Short Description:
Introduction to Drafting and AutoCAD 2D was written as a tool to guide and teach you to master AutoCAD. No two students learn at the same pace, therefore the eook was written with competency-based modules. The competency-based modules are bite-size pieces that allow you to work at your own pace. They can be used to learn by distance education, correspondence, online, instructor-lead classes, or by individuals teaching themselves to use AutoCAD in their own home or office.

Word Count: 111969

ISBN: 978-1-77420-134-3

(Note: This resource's metadata has been created automatically by reformatting and/or combining the information that the author initially provided as part of a bulk import process.)

Short Description:
This book is a tool to guide and teach you to master AutoCAD 3D. No two students learn at the same pace, therefore the book was written with competency-based modules. The competency-based modules are bite-size pieces that allows you to work at your own pace. They can be used to learn by distance education, correspondence, online, instructor-lead classes, or by individuals teaching themselves to use AutoCAD in their own home or office.

Word Count: 65964

ISBN: 978-1-77420-136-7

(Note: This resource's metadata has been created automatically by reformatting and/or combining the information that the author initially provided as part of a bulk import process.)

Short Description:
This book contains self-paced learning modules that were written as a tool to guide and teach you to master Inventor. No two students learn at the same pace, therefore, the modules were written as competency-based bite-size pieces to allow you to work at your own pace. They can be used in correspondence courses, online courses, instructor-lead classes or by individuals teaching themselves to use Inventor in their own home or office.

Word Count: 60604

(Note: This resource's metadata has been created automatically by reformatting and/or combining the information that the author initially provided as part of a bulk import process.)

An introduction to several fundamental ideas in electrical engineering and computer science, using digital communication systems as the vehicle. The three parts of the course—bits, signals, and packets—cover three corresponding layers of abstraction that form the basis of communication systems like the Internet.
The course teaches ideas that are useful in other parts of EECS: abstraction, probabilistic analysis, superposition, time and frequency-domain representations, system design principles and trade-offs, and centralized and distributed algorithms. The course emphasizes connections between theoretical concepts and practice using programming tasks and some experiments with real-world communication channels.

This course is an introductory subject in the field of electric power systems and electrical to mechanical energy conversion. Electric power has become increasingly important as a way of transmitting and transforming energy in industrial, military and transportation uses. Electric power systems are also at the heart of alternative energy systems, including wind and solar electric, geothermal and small scale hydroelectric generation.

This course provides an integrated introduction to electrical engineering and computer science, taught using substantial laboratory experiments with mobile robots. Our primary goal is for you to learn to appreciate and use the fundamental design principles of modularity and abstraction in a variety of contexts from electrical engineering and computer science.
Our second goal is to show you that making mathematical models of real systems can help in the design and analysis of those systems. Finally, we have the more typical goals of teaching exciting and important basic material from electrical engineering and computer science, including modern software engineering, linear systems analysis, electronic circuits, and decision-making.
Course Format
This course has been designed for independent study. It includes all of the materials you will need to understand the concepts covered in this subject. The materials in this course include:

Lecture videos from Spring 2011, taught by Prof. Dennis Freeman
Recitation videos, developed for OCW Scholar by teaching assistant Kendra Pugh
Course notes
Software and design labs
Homework assignments and additional exercises
Nano-quizzes and exams with solutions

Content Development
Leslie Kaelbling 
Jacob White 
Harold Abelson 
Dennis Freeman
Tomás Lozano-Pérez 
Isaac Chuang

Short Description:
This textbook emphasizes connections between theory and application, making physics concepts interesting and accessible to students while maintaining the mathematical rigour inherent in the subject. Frequent, strong examples focus on how to approach a problem, how to work with the equations, and how to check and generalize the result.

Word Count: 197484

(Note: This resource's metadata has been created automatically by reformatting and/or combining the information that the author initially provided as part of a bulk import process.)

The course is designed to provide a practical - hands on - introduction to electronics with a focus on measurement and signals. The prerequisites are courses in differential equations, as well as electricity and magnetism. No prior experience with electronics is necessary. The course will integrate demonstrations and laboratory examples with lectures on the foundations. Throughout the course we will use modern "virtual instruments" as test-beds for understanding electronics. The aim of the course is to provide students with the practical knowledge necessary to work in a modern science or engineering setting.

Word Count: 51730

(Note: This resource's metadata has been created automatically by reformatting and/or combining the information that the author initially provided as part of a bulk import process.)

Textbook covering topics orienting undergraduate-level students to the major engineering disciplines (civil, computer and electronic, and mechanical) and professionalism within these disciplines.

Students in ESD.00 work on projects to address large, complex and seemingly intractable real-world problems, such as energy supply, environmental issues, health care delivery, and critical infrastructure (e.g., telecommunications, water supply, and transportation). The course introduces interdisciplinary approaches - rooted in engineering, management, and the social sciences - to considering these critical contemporary issues. Small, faculty-led teams select an engineering systems term project to illustrate one or more of these approaches.

Short Description:
The book is most suitable for a one-term, introductory engineering thermodynamics course at the undergraduate level. It may also be used for self-learning of fundamental concepts of classical thermodynamics.

Long Description:
This open book is written with a goal to support students’ learning of fundamental concepts and engineering applications of classical thermodynamics. It features concise explanations of key concepts, step-by-step solutions to engineering examples, and interactive practice problems. The book is most suitable for a one-term, introductory engineering thermodynamics course at the undergraduate level. It may also be used as self-learning materials or a supplement to other thermodynamics books.

Word Count: 49571

(Note: This resource's metadata has been created automatically by reformatting and/or combining the information that the author initially provided as part of a bulk import process.)