# 3 Classes (36 Units)

**5.12**(12),

**6.01**(12),

**18.06**(12)

# 5.12 Organic Chemistry I

Introduction to organic chemistry. Development of basic principles to understand the structure and reactivity of organic molecules. Emphasis on substitution and elimination reactions and chemistry of the carbonyl group. Introduction to the chemistry of aromatic compounds.

This class has 3.091, and 5.111 as prerequisites.

5.12 will be offered this semester (Fall 2017). It is instructed by J. Johnson and C. Rotsides.

Lecture occurs 12:00 PM to 13:00 PM on Mondays, Wednesdays and Fridays in 32-123.

This class counts for a total of 12 credits.

You can find more information at the http://www.google.com/search?&q=MIT+%2B+5.12&btnG=Google+Search&inurl=https site or on the 5.12 Stellar site.

# 6.01 Introduction to EECS via Robotics

An integrated introduction to electrical engineering and computer science, taught using substantial laboratory experiments with mobile robots. Key issues in the design of engineered artifacts operating in the natural world: measuring and modeling system behaviors; assessing errors in sensors and effectors; specifying tasks; designing solutions based on analytical and computational models; planning, executing, and evaluating experimental tests of performance; refining models and designs. Issues addressed in the context of computer programs, control systems, probabilistic inference problems, circuits and transducers, which all play important roles in achieving robust operation of a large variety of engineered systems.

This class has 6.0001 as a prerequisite.

6.01 will be offered this semester (Fall 2017). It is instructed by A. Hartz.

Lecture occurs 9:30 AM to 11:00 AM on Tuesdays in 4-270.

This class counts for a total of 12 credits.

You can find more information at the 6.01 homepage / Fall 2008 site.

# 18.06 Linear Algebra

Basic subject on matrix theory and linear algebra, emphasizing topics useful in other disciplines, including systems of equations, vector spaces, determinants, eigenvalues, singular value decomposition, and positive definite matrices. Applications to least-squares approximations, stability of differential equations, networks, Fourier transforms, and Markov processes. Uses MATLAB. Compared with 18.700, more emphasis on matrix algorithms and many applications.

This class has 18.02 as a prerequisite.

18.06 will be offered this semester (Fall 2017). It is instructed by S. G. Johnson.

Lecture occurs 11:00 AM to 12:00 PM on Mondays, Wednesdays and Fridays in 54-100.

This class counts for a total of 12 credits.

You can find more information at the http://www.google.com/search?&q=MIT+%2B+18.06&btnG=Google+Search&inurl=https site or on the 18.06 Stellar site.