# 3 Classes (36 Units)

**6.006**(12),

**6.01**(12),

**6.042**(12)

# 6.006 Introduction to Algorithms

Introduction to mathematical modeling of computational problems, as well as common algorithms, algorithmic paradigms, and data structures used to solve these problems. Emphasizes the relationship between algorithms and programming, and introduces basic performance measures and analysis techniques for these problems.

This class has 6.042, 6.0001, and 6.009 as prerequisites.

6.006 will be offered this semester (Fall 2019). It is instructed by J. Ku.

Lecture occurs 11:00 AM to 12:00 PM on Tuesdays and Thursdays in 26-100.

This class counts for a total of 12 credits.

You can find more information on MIT OpenCourseWare at the Introduction to Algorithms site or on the 6.006 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 not be offered this semester. It will be available in the Spring semester, and will be instructed by T. Lozano-Perez, A. Hartz, L. P. Kaelbling and D. M. Freeman.

Lecture occurs 9:30 AM to 11:00 AM on Mondays in 32-144.

This class counts for a total of 12 credits.

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

# 6.042 Mathematics for Computer Science

Elementary discrete mathematics for computer science and engineering. Emphasis on mathematical definitions and proofs as well as on applicable methods. Topics include formal logic notation, proof methods; induction, well-ordering; sets, relations; elementary graph theory; asymptotic notation and growth of functions; permutations and combinations, counting principles; discrete probability. Further selected topics include recursive definition and structural induction, state machines and invariants, integer congruences, recurrences, generating functions.

This class has 18.01 as a prerequisite.

6.042 will be offered this semester (Fall 2019). It is instructed by F. T. Leighton,  Z. R. Abel and  A. Moitra.

Lecture occurs 2:30 PM to 4:00 PM on Tuesdays and Thursdays in 26-100.

This class counts for a total of 12 credits.

You can find more information on MIT OpenCourseWare at the Mathematics for Computer Science site or on the 6.042 Stellar site.