Nearly all of the courses allow students to download lectures, and some of … We have lectures devoted to principles of engineering system design which will take you through the basics of how computer science … View Website Partha lost his battle with cancer in October of 2010, ... Law School Lectures (audio) The University of Chicago Law School Today, close to 1,000 schools around the world have created thousands of free online courses. Paul Summers, Engineering & Computer Science— Birmingham City University. A broad and robust understanding of computer science and programming How to think algorithmically and solve programming problems efficiently Concepts like abstraction, algorithms, data structures, … Explore our catalog of online degrees, certificates, Specializations, & MOOCs in data science, computer science, business, health, and dozens of other topics. 0; JEE & NEET. Global Arctic from École Polytechnique Fédérale de Lausanne. Skip to Navigation. 6.0001 - Introduction to Computer Science and Programming in Python, 6.0002 - Introduction to Computational Thinking and Data Science, 6.00SC - Introduction to Computer Science and Programming, 6.00 - Introduction to Computer Science and Programming, 6.001 - Structure and Interpretation of Computer, 6.01SC - Introduction to Electrical Engineering & Computer Science I, 6.02 - Introduction to EECS II: Digital Communication Systems, 6.006 - Introduction to Algorithms (Fall 2011), 6.033 - Computer System Engineering (SMA 5501), 6.035 - Computer Language Engineering (SMA 5502), 6.041 - Probabilistic Systems Analysis and Applied Probability, 6.042J - Mathematics for Computer Science (Fall 2010), 6.046J - Introduction to Algorithms (Fall 2005) (SMA 5503), 6.046J - Design and Analysis of Algorithms (Spring 2015), 6.172 - Performance Engineering of Software Systems, MAS.S62 Cryptocurrency Engineering and Design, CS 61A - The Structure and Interpretation of Computer Programs, CS 61B - Data Structures and Advanced Programming, CS 70 - Discrete Mathematics and Probability Theory (Spring 2015), CS 70 - Discrete Mathematics and Probability Theory (Fall 2012), CS 162 - Operating Systems and System Programming, CS 164 - Programming Languages and Compilers (Spring 2012), CS 170 - Efficient Algorithms and Intractable Problems, CS 184 - Fundamentals of Computer Graphics, CS 186 - Introduction to Database Systems, CS 188 - Introduction to Artificial Intelligence (Spring 2015), CS 188 - Introduction to Artificial Intelligence (Fall 2011), CS 194 - Advanced Operating Systems Structures and Implementation, CS 195 - Social Implications of Computing, CS C149 - Introduction to Embedded Systems, CS 267 - Applications of Parallel Computers (Spring 2015), CS 267 - Applications of Parallel Computers (Spring 2017), CS 294 - Deep Reinforcement Learning (Spring 2017), CS547 - Human-Computer Interaction Seminar, Bits: The Computer Science of Digital Information, CS 50: Introduction to Computer Science I, CS E-1: Understanding Computers and the Internet, CS E-259: XML with Java, Java Servlet, and JSP, CPSC 340 - Machine Learning and Data Mining (2012, UBC), Machine Learning (2015, University of Oxford), CPSC 322 - Introduction to Artificial Intelligence (2013, UBC), CS 156 - Machine Learning Course (Spring 2012), ECS 124 - Fundamental Algorithms in Bioinformatics, ECS 275A - Ray Tracing for Global Illumination, Digital Circuits and Systems (Prof. S. Srinivasan, IIT Madras), Digital Circuits and Systems (Prof. Shankar Balachandran, IIT Madras), Computer Architecture (Prof. Anshul Kumar, IIT Delhi), Computer Architecture (Prof. Mainak Chaudhuri, IIT Kanpur), Computer Architecture (Prof. Smruti R.Sarangi, IIT Delhi), Computer Architecture (Prof.Madhu Mutyam, IIT Madras), Multi-core Computer Architecture: Storage and Interconnects, Introduction to Industry 4.0 and Industrial Internet of Things, Performance Evaluation of Computer Systems, Introduction to Human Computer Interaction, Introduction to Modern Application Development, Design and Pedagogy of the Introductory Programming Course, Programming Methodology and Data Structures, Programming and Data Structure (Dr. N S. Narayanaswamy, IIT Madras), Programming, Data Structures and Algorithms in Python, Programming, Data Structures and Algorithms, An Introduction to Algorithms and Analysis, Fundamental Algorithms: Design and Analysis, Design and Analysis of Algorithms (IIT Bombay), Design and Analysis of Algorithms (Chennai Mathematical Institute), Artificial Intelligence (Prof. P. Dasgupta, IIT Kharagpur), Artificial Intelligence (Prof. Anupam Basu, IIT Kharagpur), Artificial Intelligence (Prof. Deepak Khemani, IIT Madras), Artificial Intelligence: Knowledge Representation and Reasoning, Introduction to Machine Learning (Prof. S. Sarkar, IIT Kharagpur), Introduction to Machine Learning (Dr. Balaraman Ravindran, IIT Madras), Pattern Recognition (Prof. Sukhendu Das, IIT Madras), Pattern Recognition (Prof. P.S. Free Audio Lectures. The combination of technical and soft skills we provide mean that you will be ready for employment immediately after graduation. 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