4 Classes (48 Units)

6.036 (12), 7.03 (12), 7.05 (12), 9.40 (12)

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6.036 Introduction to Machine Learning

Class Info

Introduces principles, algorithms, and applications of machine learning from the point of view of modeling and prediction; formulation of learning problems; representation, over-fitting, generalization; clustering, classification, probabilistic modeling; and methods such as support vector machines, hidden Markov models, and Bayesian networks. Students taking graduate version complete additional assignments. Meets with 6.862 when offered concurrently. Enrollment may be limited.

This class has 6.0001 as a prerequisite.

6.036 will be offered this semester (Fall 2017). It is instructed by T. S. Jaakkola, L. P. Kaelbling and T. Lozano-Perez.

Lecture occurs 2:30 PM to 4:00 PM on Mondays and Wednesdays in 34-501.

This class counts for a total of 12 credits.

You can find more information at the http://www.google.com/search?&q=MIT+%2B+6.036&btnG=Google+Search&inurl=https site.

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7.03 Genetics

Class Info

The principles of genetics with application to the study of biological function at the level of molecules, cells, and multicellular organisms, including humans. Structure and function of genes, chromosomes, and genomes. Biological variation resulting from recombination, mutation, and selection. Population genetics. Use of genetic methods to analyze protein function, gene regulation, and inherited disease.

This class has 7.01x as a prerequisite.

7.03 will be offered this semester (Fall 2017). It is instructed by P. Gupta and P. Reddien.

Lecture occurs 11:00 AM to 12:00 PM on Mondays, Wednesdays and Fridays in 4-370.

This class counts for a total of 12 credits.

You can find more information at the MIT + 7.03 - Google Search site or on the 7.03 Stellar site.

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7.05 General Biochemistry

Class Info

Contributions of biochemistry toward an understanding of the structure and functioning of organisms, tissues, and cells. Chemistry and functions of constituents of cells and tissues and the chemical and physical-chemical basis for the structures of nucleic acids, proteins, and carbohydrates. Basic enzymology and biochemical reaction mechanisms involved in macromolecular synthesis and degradation, signaling, transport, and movement. General metabolism of carbohydrates, fats, and nitrogen-containing materials such as amino acids, proteins, and related compounds.

This class has 5.12, and 7.01x as prerequisites.

7.05 will not be offered this semester. It will be available in the Spring semester, and will be instructed by M. Vander Heiden and M. Yaffe.

Lecture occurs 9:30 AM to 11:00 AM on Mondays, Wednesdays and Fridays in 10-250.

This class counts for a total of 12 credits.

You can find more information at the http://www.google.com/search?&q=MIT+%2B+7.05&btnG=Google+Search&inurl=https site or on the 7.05 Stellar site.

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9.40 Introduction to Neural Computation

Class Info

Introduces quantitative approaches to understanding brain and cognitive functions. Topics include mathematical description of neurons, the response of neurons to sensory stimuli, simple neuronal networks, statistical inference and decision making. Also covers foundational quantitative tools of data analysis in neuroscience: correlation, convolution, spectral analysis, principal components analysis. Mathematical concepts include simple differential equations and linear algebra.

This class has 6.0002, and 9.01 as prerequisites.

9.40 will not be offered this semester. It will be available in the Spring semester, and will be instructed by M. Fee.

Lecture occurs 10:30 AM to 12:00 PM on Tuesdays and Thursdays in 46-3002.

This class counts for a total of 12 credits.

You can find more information at the http://www.google.com/search?&q=MIT+%2B+9.40&btnG=Google+Search&inurl=https site or on the 9.40 Stellar site.

MIT 9.40 Introduction to Neural Computation Related Textbooks

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