M.I.T. Game-Changer: Free Online Education For All. Python Programming Tutorial - 4 - Modules and Functions. Thenewboston's Channel. 1.03_Object Orientation 2 - Relationships. 6.00 Introduction to Computer Science and Programming, Fall 2008. 6.001 Structure and Interpretation of Computer Programs, Spring 2005.
Introduction to Neural Networks. CS-449: Neural Networks Fall 99 Instructor: Genevieve Orr Willamette University Lecture Notes prepared by Genevieve Orr, Nici Schraudolph, and Fred Cummins [Content][Links] Course content Summary Our goal is to introduce students to a powerful class of model, the Neural Network.
We then introduce one kind of network in detail: the feedforward network trained by backpropagation of error. Lecture 1: Introduction Lecture 2: Classification Lecture 3: Optimizing Linear Networks Lecture 4: The Backprop Toolbox Lecture 5: Unsupervised Learning Lecture 6: Reinforcement Learning Lecture 7: Advanced Topics [Top] Review for Midterm: Links Tutorials: The Nervous System - a very nice introduction, many pictures Neural Java - a neural network tutorial with Java applets Web Sim - A Java neural network simulator. a book chapter describing the Backpropagation Algorithm (Postscript) A short set of pages showing how a simple backprop net learns to recognize the digits 0-9, with C code Reinforcement Learning - A Tutorial.
9.641 Intro to Neural Networks Video Lectures. Lecture schedule. Chemical Engineering - Biochemical Engineering. Chemistry and Biochemistry - Eukaryotic Gene Expression - basics and benefits. NPTEL PHASE 2 - Courses. Special Issue: Synthetic Biology. Imperial College/Courses/Spring2008/Synthetic Biology/Syllabus. Laboratory Fundamentals of Synthetic Biology. From OpenWetWare Syllabus Class Format The Class will meet twice a week, one 2 hour classroom session, and one 3 hour lab session.
Problem sets will be assigned weekly for the first eight weeks. A midterm exam will cover the classroom material and the first several weeks of lab instruction. Grades The final grade will be as follows: 20% Problem Sets 30% Midterm Exam 20% Lab Evaluations 30% Final Project Schedule Introduction - Synthetic Biology: History, current applications and future directions Powerpoint (w/content from Drew Endy) Assignments: Endy Article and Comic Strip The Biology (4 sessions) Cells, DNA, RNA and Protein DNA - information encoding, structure, sequencing and synthesis RNA - encoding, structure, function (RNA Enzymes, RNA Aptamers) Proteins - Crystallography, functions, scaffolds Introductory packet about DNA, RNA, Protein.
Create a biobrick out of a sequence (force them to re-optimize a coding region into e. coli and remove a biobrick incompatibility). Reading List. Synbio 2007. From OpenWetWare General Info Spring 2007 Instructor: Jay Keasling (keasling@berkeley.edu) GSI: Jeffrey Dietrich (jadietrich@gmail.com) Logistics: Lecture/Discussion: 2 hours, 10-12 AM Friday Grading: Literature Review 30% Group Project 60% Class Participation 10% Office hours: contact Jeffrey Dietrich to arrange a meeting Announcements ASSIGNMENT (Due 2/16): email Jeff with your three top choices for topics to lead in literature review group discussion.
Tentative Schedule 1/19 Introduction, Basis for Synthetic Biology - Jay Keasling 1/26 Modeling and Design of Synthetic Systems - Adam Arkin Genetic models, stochastic and continuous simulations, adaption of circuit methods to SB. 2/2 Drugs from Bugs-Jay Keasling 2/9 Design of Tumor-Killing Bacteria - J. 5.95J Teaching College-Level Science and Engineering, Spring 2009. Free Online Course Materials. Free Online Course Materials. Free Online Course Materials. Free Online Course Materials. Free Online Course Materials. Free Online Course Materials. Free Online Course Materials. Free Online Course Materials.