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Wednesday, June 28, 2006

Engineering Video Lectures

Initially my goal was to focus just on physics, maths and computer science lectures but I have been getting emails lately asking me to post other lectures as well.

Here are all the engineering lectures I could find:


Circuits and Electronics
6.002 introduces the fundamentals of the lumped circuit abstraction. Topics covered include: resistive elements and networks; independent and dependent sources; switches and MOS transistors; digital abstraction; amplifiers; energy storage elements; dynamics of first- and second-order networks; design in the time and frequency domains; and analog and digital circuits and applications. Design and lab exercises are also significant components of the course. 6.002 is worth 4 Engineering Design Points.


Linear Integrated Circuits
This course will focus on the design of MOS analog integrated circuits with extensive use of Spice for the simulations. In addition, applications of analog integrated circuits will be covered which may include such topics as RF amplification, discrete and continuous time filtering and A/D conversion. Though the focus will be on MOS implementations, comparison with bipolar circuits will be given.


Digital Integrated Circuits

This course is an introduction to digital integrated circuits. The material will cover CMOS devices and manufacturing technology along with CMOS inverters and gates. Other topics include propagation delay, noise margins, power dissipation, and regenerative logic circuits. We will look at various design styles and architectures as well as the issues that designers must face, such as technology scaling and the impact of interconnect. Examples presented in class include arithmetic circuits, semiconductor memories, and other novel circuits.

The course will start with a detailed description and analysis of the core digital design block, the inverter. Implementations in CMOS will be discussed. Next, the design of more complex combinational gates such as NAND, NOR and EXORs will be discussed, looking at optimizing the speed, area, or power. The learned techniques will be applied on more evolved designs such as adders and multipliers. The influence of interconnect parasitics on circuit performance and approaches to cope with them are treated in detail. Substantial attention will then be devoted to sequential circuits, clocking approaches and memories. The course will be concluded with an examination of design methodologies.


Integrated Circuits for Communications
Analysis and design of electronic circuits for communication systems, with an emphasis on integrated circuits for wireless communication systems. Analysis of noise and distortion in amplifiers with application to radio receiver design. Power amplifier design with application to wireless radio transmitters. Class A, Class B, and Class C power amplifiers. Radio-frequency mixers, oscillators, phase-locked loops, modulators, and demodulators.


Advanced Analog Integrated Circuits
Analysis and optimized design of monolithic operational amplifiers and wide-band amplifiers; methods of achieving wide-band amplification, gain-bandwidth considerations; analysis of noise in integrated circuits and low noise design. Precision passive elements, analog switches, amplifiers and comparators, voltage reference in CMOS circuits. Nonidealities: noise, matching, supply/io/substrate coupling.


Advanced Digital Integrated Circuits
This course aims to convey a knowledge of advanced concepts of circuit design for digital VLSI components in state of the art MOS technologies. Emphasis is on the circuit design, optimization, and layout of either very high speed, high density or low power circuits for use in applications such as micro-processors, signal and multimedia processors, memory and periphery. Special attention will devoted to the most important challenges facing digital circuit designers today and in the coming decade, being the impact of scaling, deep submicron effects, interconnect, signal integrity, power distribution and consumption, and timing.

This semester, extra focus will be given to the following topics: Low power and low-voltage, process variations and robustness, and memory design in the nanoscale era. This will reflected in both the lectures and the preferred projects.


Principles of Digital Communications II
This course is the second of a two-term sequence with course 6.450. The focus is on coding techniques for approaching the Shannon limit of additive white Gaussian noise (AWGN) channels, their performance analysis, and design principles. After a review of 6.450 and the Shannon limit for AWGN channels, the course begins by discussing small signal constellations, performance analysis and coding gain, and hard-decision and soft-decision decoding. It continues with binary linear block codes, Reed-Muller codes, finite fields, Reed-Solomon and BCH codes, binary linear convolutional codes, and the Viterbi algorithm.

More advanced topics include trellis representations of binary linear block codes and trellis-based decoding; codes on graphs; the sum-product and min-sum algorithms; the BCJR algorithm; turbo codes, LDPC codes and RA codes; and performance of LDPC codes with iterative decoding. Finally, the course addresses coding for the bandwidth-limited regime, including lattice codes, trellis-coded modulation, multilevel coding and shaping. If time permits, it covers equalization of linear Gaussian channels.


Nano-to-Nano Transport Processes (Audio only)
This course provides parallel treatments of photons, electrons, phonons, and molecules as energy carriers, aiming at fundamental understanding and descriptive tools for energy and heat transport processes from nanoscale continuously to macroscale. Topics include the energy levels, the statistical behavior and internal energy, energy transport in the forms of waves and particles, scattering and heat generation processes, Boltzmann equation and derivation of classical laws, deviation from classical laws at nanoscale and their appropriate descriptions, with applications in nano- and microtechnology.


Signals and Systems
Course covers: Continuous and discrete-time transform analysis techniques with illustrative applications. Linear and time-invariant systems, transfer functions. Fourier series, Fourier transform, Laplace and Z-transforms. Sampling and reconstruction. Solution of differential and difference equations using transforms. Frequency response, Bode plots, stability analysis. Illustrated by analysis of communication systems and feedback control systems.


Structure and Interpretation of Signals and Systems
This course is an introduction to mathematical modeling techniques used in the design of electronic systems. An important keyword here is "mathematical."

Signals are defined as functions on respective sets. Examples include:
· Continuous-time signals (audio, radio, voltages);
· Discrete-time signals (digital audio, synchronous circuits);
· Images (discrete and continuous);
· Discrete-event signals; and
· Sequences.

Systems are defined as mappings on signals. The notion of the state is discussed in a general way. Feedback systems and automata illustrate alternative approaches to modeling state in systems.

Automata theory is studied using Mealy machines with input and output. Notions of equivalence of automata and concurrent composition are introduced.

Hybrid systems combine time-based signals with event sequences.

Difference and differential equations are considered as models for linear, time-invariant state machines.

Frequency domain models for signals and frequency response for systems are investigated.

Sampling of continuous signals is discussed to relate continuous time and discrete time signals.

Applications include communications systems, audio, video, and image processing systems, and control systems.


Digital Image Processing
Course covers:
1. Image reconstruction from partial information
2. Two-dimensional (2-D) Fourier transform and z-transform;
3. 2-D DFT and FFT, FIR and IIR filter design and implementation.
4. Basics of Image Processing techniques and perception;
5. Image and video enhancement
6. Image and video restoration
7. Reconstruction from multiple images
8. Image and video analysis: Image Representation and models; image and video classfication and segmentation; edge and boundary detection in images
9. Image compression and coding
10. Video compression
11. Image and Video Communication, storage and retreival
12. Image and video rendering and assessment
13. Image and video Acquisition
14. Applications of image processing: Synthetic Aperture Radar, computed tomography, cardiac image processing, finger print classfication, human face recognition.


Digital Signal Processing
Course covers:
1. Fast review of LTI systems, DTFT, sampling.
2. Multirate signal processing, Bilateral Z Transform.
3. Discrete Fourier transform, Fast Fourier Transform.
4. Quantization, finite word length effects
5. FIR and IIR filter design techniques;
6. Filter banks, Wavelets
7. Applications: speech and video processing.


Analysis and Design of VLSI Analog-Digital Interface Integrated Circuits
Analog circuits are increasingly part of larger chips containing both analog and digital circuits. In this course, we look at the architecture of these chips, the representation of signals in the analog and digital domain, filtering, conversion with analog/digital and digital/analog converters. Constraints such as maximum signal handling capability, electronic noise, frequency limitations, and tradeoffs among these factors are discussed. Variety of communication systems utilizing analog-digital interface circuitry is covered. The key concepts discussed in the course are:

Areas of discussion:
- Filters
- Continuous time filters- biquads and ladder type filters
- Biquads & ladder
- Opamp-RC, Opamp-Mosfet-C, gm-C filters
- Automatic frequency tuning
- Switched capacitor (SC) filters
- Data Converters
- D/A converter architectures
- A/D converter
- Nyquist rate ADC- Flash, Pipeline ADCs,….
- Oversampled converters
- Self-calibration techniques
- Communication systems utilizing analog/digital interfaces
- Wireline communication systems- ISDN, XDSL…
- Wireless communication systems- Wireless LAN, Cellular telephone,…
- Disk drive electronics
- Fiber-optics systems


Solid State Devices
Course covers:
MOS conductors, MOS transistors, MOSFET, MOSFET issues, Off and On State Effects, Universal Mobility Curve and Velocity Saturation, Hot Carrier Effects, International Technology Roadmap for Semiconductors, Physics of Basic Oxide Reliability; High-K Dielectrics, Oxides, Gate Electrode Materials, Strained Silicone, SOI, Multiple-Gate MOSFIT, Multiple Gate Devices; Memory, Memory and Displays.


Introduction to MEMS (Micro-Electro-Mechanical Systems) Design
Course covers: Basic IC/MEMS Fabrication, Deposition, Etching, Surface & Bulk Micromachining, Beams, Gaps, Resonators, Better Approximations: Parallel Plates, Couette Damping, Squeeze Film Damping, Effective Mass, Electrostatic, Electrostatic Pull-in; Thermal Conductivity, Thermal Capacity, Thermal Time Constant, Foundry Processes


Electromagnetics and Applications
This course explores electromagnetic phenomena in modern applications, including wireless communications, circuits, computer interconnects and peripherals, optical fiber links and components, microwave communications and radar, antennas, sensors, micro-electromechanical systems, motors, and power generation and transmission. Fundamentals covered include: quasistatic and dynamic solutions to Maxwell's equations; waves, radiation, and diffraction; coupling to media and structures; guided and unguided waves; resonance; and forces, power, and energy.

Note: This course provides only demonstrations of different electromagnetic phenomena and does not provide full video lectures


Electromagnetic Fields, Forces, and Motion
6.641 examines electric and magnetic quasistatic forms of Maxwell's equations applied to dielectric, conduction, and magnetization boundary value problems. Topics covered include: electromagnetic forces, force densities, and stress tensors, including magnetization and polarization; thermodynamics of electromagnetic fields, equations of motion, and energy conservation; applications to synchronous, induction, and commutator machines; sensors and transducers; microelectromechanical systems; propagation and stability of electromechanical waves; and charge transport phenomena.

Note: Only demonstrations used throughout the course to convey electromagnetism concepts are provided.


Atomistic Computer Modelling of Materials
This course uses the theory and application of atomistic computer simulations to model, understand, and predict the properties of real materials. Specific topics include: energy models from classical potentials to first-principles approaches; density functional theory and the total-energy pseudopotential method; errors and accuracy of quantitative predictions: thermodynamic ensembles, Monte Carlo sampling and molecular dynamics simulations; free energy and phase transitions; fluctuations and transport properties; and coarse-graining approaches and mesoscale models. The course employs case studies from industrial applications of advanced materials to nanotechnology. Several laboratories will give students direct experience with simulations of classical force fields, electronic-structure approaches, molecular dynamics, and Monte Carlo.


Aircraft Systems Engineering
16.885J offers a holistic view of the aircraft as a system, covering: basic systems engineering; cost and weight estimation; basic aircraft performance; safety and reliability; lifecycle topics; aircraft subsystems; risk analysis and management; and system realization. Small student teams retrospectively analyze an existing aircraft covering: key design drivers and decisions; aircraft attributes and subsystems; and operational experience. Oral and written versions of the case study are delivered. For the Fall 2005 term, the class focuses on a systems engineering analysis of the Space Shuttle. It offers study of both design and operations of the shuttle, with frequent lectures by outside experts. Students choose specific shuttle systems for detailed analysis and develop new subsystem designs using state of the art technology.


Soft X-Rays and Extreme Ultraviolet Radiation
Course covers: Interaction Physics, Radiation by an Accelerated Charge: Scattering by Free and Bound Electrons, Multi-Electron Atom, Atomic Scattering Factors: Wave Propagation and Refractive Index, Refraction and Reflection, Total Internal Reflection, Brewster's Angle, K-K, Multilayer Interference Coatings, Scattering, Reflectivity, Multilayer Mirrors, Coating Process, Applications, Intro Synchrotron Radiation, Bending Magnet Radiation, Undulator Radiation, Undulator Equation, Central Radiation Cone, Undulator Radiated Power, Electron Beam Parameters, Spectral Brightness of Undulator Radiation, Harmonics, Wiggler Radiation, Physics of Plasmas, Basic Parameters, Fluid and Kinetic Descriptions, Line and Continuum Radiation, Waves in a Plasma, Waves in a Plasma, Black-Body Radiation; Plasma Sources, Laser-Produced and Discharge Plasmas: Compact Plasma Sources, High Harmonic Generation, Basic Processes, Quasi-Phasematching, EUV and Soft X-Ray Lasers, Basic Lasing Process, Ne- Like and Ni- Like Lasers, Refractive Effects, Compact EUV Lasers, Cross-Sections, Spectral Bandwidth, Gain, Wavelength Scaling, Spatial and Temporal Coherence, Spatial and Spectral Filtering, Coherent Undulator Radiation, Van Cittert-Zernike; Coherence Experiments, Zone Plate Formulas, Diffraction by Zone Plates and Pinholes, Resolution, DOF, Zone Plate Diffraction, Coherence Issues, Applications of Zone Plate Microscopy, EUV Lithography, Student Projects

posted by Peteris Krumins at 4:43 PM | 25 comments

Monday, June 26, 2006

More Mathematics and Theoretical Computer Science Video Lectures

Here are the additional video lectures in mathematics (and theoretical computer science) which were in my bookmarks. I still have many links left to check so visit my blog in a few days for updates.

Lectures are ordered by their complexity.

Algebra Review
  • Video Lectures: Math 160 (University of Idaho)
Course covers: factoring, interval notation, definition of function, functions, piece-wise defined functions, function composition, quadratic functions, solving quadratic functions. Slope of the line, equation of the line, parallel and perpendicular lines. Law of exponents, properties of logarithms. Applications to exponential function, exponential growth and decay. Solving systems of equations by substitution and elimination.


Intermediate AlgebraThe primary purpose of Intermediate Algebra is to improve your skills and competency in algebra so that you will be successful in calculus, the other math courses required for your major, and in the courses that use mathematics. Another goal is to help you develop your mathematical learning skills so that you will be more confident in future mathematical courses.

Course covers: the real numbers, linear equations, linear inequalities and absolute value, linear equations and inequalities in two variables, systems of linear equations, exponents, polynomials and polynomial functions, factoring, rational expressions, roots and radicals, quadratic equations and inequalities.


Elementary Statistics
Elementary Statistics is an introduction to data analysis course that makes use of graphical and numerical techniques to study patterns and departures from patterns. The student studies randomness with emphasis on understanding variation, collects information in the face of uncertainty, checks distributional assumptions, tests hypotheses, uses probability as a tool for anticipating what the distribution of data may look like under a set of assumptions, and uses appropriate statistical models to draw conclusions from data.

The course introduces the student to applications in engineering, business, economics, medicine, education, the sciences, and other related fields. The use of technology (computers or graphing calculators) will be required in certain applications.

Course covers: Sampling and data. Statistical graphs, quartiles and percentiles, mean, median, mode, variance and standard deviation. Basic probability, independent and dependent events, addition and multiplication rules. Discrete random variables, discrete probability distribution functions, expected value, binomial probability distribution function. Continuous random variables, continuous probability distribution functions, uniform probability distribution, exponential probability distribution. The normal probability distribution function, standard normal probability density function. Central limit theorem for averages and sums. Confidence intervals. Hypothesis testing. The Chi-Square distribution function. Linear regression and correlation.



Applied Probability (5 lectures)
Focuses on modeling, quantification, and analysis of uncertainty by teaching random variables, simple random processes and their probability distributions, Markov processes, limit theorems, elements of statistical inference, and decision making under uncertainty. This course extends the discrete probability learned in the discrete math class. It focuses on actual applications, and places little emphasis on proofs. A problem set based on identifying tumors using MRI (Magnetic Resonance Imaging) is done using Matlab.


Finite Mathematics with Applications
  • Video Lectures: Math 1313 (University of Houston)
Course covers slopes, equations and graphing of lines, linear depreciation, cost, revenue and profit functions, intersection of lines, break-even analysis, the method of least squares, graphing linear inequalities, graphing systems of linear inequalities, linear programming problems, graphical solution of linear problems, simple interest, future value, present value, and effect rate, annuities, amortization and sinking funds. Set notation and terminology, set operations, Venn diagrams, number of elements in a set, the multiplication rule, permutations and combinations. Experiments, events and sample spaces, definition of probability, rules of probability, use of counting technique, conditional probability, independent events, Bayes' theorem, distributions of random variables, expected value, odds, variance and standard deviation, Chebyshev's inequality, the binomial distribution, the normal distribution, applications of the normal distribution.


Trigonometry for Calculus
The goal of this course is to prepare you for the trigonometry that you will encounter in calculus. During this one credit course in trigonometry, you will learn how to evaluate trigonometric functions, sketch the graphs of the sine, cosine and tangent functions, study the inverse trigonometric functions and much more.

Course covers the Cartesian coordinate system, functions, angle and radian measure, special right triangles, the unit circle, the trigonometric ratios, graphs of trig. ratios, periodic functions, fundamental trigonometric identities and inverse trigonometric functions.


Introduction to Mathematical Computation
Throughout the course we will illustrate application of software in typical undergraduate mathematical subjects such as calculus, probability, linear algebra, and number theory. Further, we will move to structural programming. We conclude the course by illustrating elements of contemporary platform independent language, java. No programming experience required

Course covers: Basic commands in Mathematica, Mathematica in Calculus, Mathematica in Probability, Mathematica and Linear Algebra, Mathematica and Number Theory, Mathematica and structural programming, Introduction to Java.


Note: Links to lectures 6 - 17 are missing. You can access them by changing the last number of the link to the first 5 lectures. Example: to access lecture 12 use address http://130.212.40.150:8080/ramgen/mathematica/lecture12.rm, etc.


Pre-Calculus and Introduction to Analytic Geometry
The primary purpose of Pre-Calculus and Analytic Geometry is to improve your skills and competency in algebra so that you will be successful in calculus, the other math courses required for your major, and in the courses that use mathematics. Another goal is to help you develop your mathematical learning skills so that you will be more confident in future mathematical courses.

Course covers: equations and identities, graphs, functions and their graphs, polynomial and rational functions, exponential and logarithmic functions, analytic geometry.


First Year Calculus (Calculus I)
The central object of the study in calculus is the concept of a function. Functions are used to describe the real world around us. Calculus introduces two fundamental concepts which enable us to describe and investigate functions. These are: the derivative and the integral. The derivative describes the behavior of a function at a particular time. The integral carries information about the history of a function.

Course covers: limits, limit laws, continuity, limits involving infinity, rates of change, derivatives, differentiation rules, product and quotient rules, rates of change in science, derivatives of trigonometric functions, the chain rule, implicit differentiation, logarithmic differentiation, maxima and minima, mean value theorem, L'Hospital's rule, optimization problems, areas and distances, definite integral, fundamental theorem of calculus.


Business Calculus
  • Video Lectures: Math 1314 (University of Houston)

Course covers limits, one-sided limits and continuity, the derivative, basic rules of differentiation, the product and quotient rules, the chain rule, higher order derivatives, basic applications of derivative, marginal functions in economics, applications of the first derivative, applications of the second derivative, curve sketching, absolute extrema, optimization, applications with exponential functions, antiderivatives, integration by substitution, area under the curve - Riemann Sums, the fundamental theorem of calculus, evaluation of definite integral, area between two curves, functions of several variables, partial derivatives, relative extrema.


Mathematical Writing (by Donald E. Knuth!)
Issues of technical writing and the effective presentation of mathematics and computer science. Preparation of theses, papers, books, and "literate" computer programs.

"I also gave a class called Mathematical Writing, just for one quarter," says Knuth. "The lectures are still of special interest because they feature quite a few important guest lecturers." This collection contains thirty-one tapes.


Mathematics and Computer Science Problem Seminar (by Donald E. Knuth!)
During the course students with Professor Knuth solve 5 problems which have not been solved.
According to D. E. Knuth course is given only once in two years because it takes him two years to think of good enough problems. The goal of the course it to understand problem solving in general and not just to solve those 5 problems and to get into as many of the different areas of computer science research as possible.

"This was an experimental project where we'd have three or four cameras in a basement studio and we would film classes of about an hour," says Knuth. "We got a bunch of our brightest students and gave them extremely difficult problems. You could literally see the Aha taking place. People can watch the problem-solving process as it occurred." Over 25 hours of these sessions are available for viewing.


Dynamical Systems and Chaos
The course will provide quick introduction to Dynamical Systems, Ergodic Theory and Chaos. We will start with examples of dynamical systems, with basic notions such as orbits, periodic points, phase portraits, attraction and repulsion, calculus of fixed points, invariant measures, Bernoulli shifts and ergodic theorems of various types.
Then we will study bifurcations on the example of dynamics of quadratic maps. The quadratic family will be used to demonstrate the transition to chaos and the main features of chaotic behaviour. We will touch Sarkovsii's Theorem and Newton's Method.

Elements of Symbolic Dynamics and subshifts of finite type will be considered. Then we will move to fractals and discuss fractal dimension and related topics. After that we will introduce Holomorphic Dynamics and the main objects such as Julia sets and the Mandelbrot set. Time permitting, we will consider some rational maps in dimension two and higher. Henon map will be considered, as well as some maps arising in the theory of fractal groups, and the Smale horse shoe map. We will consider also spectra and spectral measures related to such groups and to fractal sets like Sierpinski gasket or Cantor set.


Computer Musings Lecture Series (by Donald E. Knuth)

“These lectures I'’ve given have been inspired and shaped by the questions and responses of the audiences to whom I spoke, and I want to keep them alive,prof. D.E.Knuth explains. We'’ve got these tapes and the world is going digital; Stanford Centre for Professional Development has the talent and expertise to convert them. I feel that archiving is important. I'’ve learned from archived lectures and classes myself, so I think others can learn from these.

A sampling of musings includes:
  • Dancing Links
  • Fast Input/Output with Many Disks, Using a Magic Trick
  • MMIX: A RISC Computer for the New Millennium
  • The Joy of Asymptotics
  • Bubblesort at random (one-dimensional particle physics)
  • Trees, Forests, and Polyominoes
  • Finding all spanning trees


"Other" Donald E. Knuth Lectures

Also available are two five-session short courses about TeX (1981); twelve lectures about the implementation of TeX (1982); video recordings of eight history sessions about Computer Science at Stanford, taped in 1987 and featuring many alumni of our department; and some reminiscences by Professors Feigenbaum, Floyd, Golub, Herriot, Knuth, McCarthy, Miller, and Wiederhold about the founding of Stanford's Computer Science Department, The Living Legends (1997).

Questions from audience and students are important to the learning process, according to Knuth. Sometimes the expression of a more mature idea isn't the most interesting or effective way to learn you may learn more from how a professor reacts to an idea or a question. He pauses, and then adds, People might learn a lot from watching me fumble around to answer a question.


Related Posts

  • Free Mathematics Video Courses
    (Includes courses: discrete mathematics, algebra, linear algebra, mathematical problems, differential equations and math methods for engineers)

  • Mathematics Video Lectures
    (Includes course practice of mathematics and lots of mathematics seminar videos in applied maths, geometry/topology, liquid flow and string theory)

  • Mathematics Video Lectures
    (Includes calculus, vector calculus, tensors, the most important concepts of mathematics, basic mathematics, numerical methods, p=np problem, randomness, fractals and splines and various lectures from advanced institute for study.)

posted by Peteris Krumins at 7:20 PM | 14 comments

Saturday, June 24, 2006

Free Computer Science Video Lecture Courses

Here is a list of video lectures in computer science I had collected over the years.
This list is only two-thirds of all links I have in my bookmarks, I will go through the rest of links later. Check back.

For formal computer science education here is an overview of a bachelor degree in computer science.


Web Applications
Teaches basics of designing a dynamic web site with a database back end, including scripting languages, cookies, SQL, and HTML with the goal of building such a site as the main (group) project Emphasizes computer-human interface and the graphical display of information.


Structure and Interpretation of Computer Programs
Structure and Interpretation of Computer Programs has been MIT's introductory pre-professional computer science subject since 1981. It emphasizes the role of computer languages as vehicles for expressing knowledge and it presents basic principles of abstraction and modularity, together with essential techniques for designing and implementing computer languages. This course has had a worldwide impact on computer science curricula over the past two decades.


Structure and Interpretation of Computer Programs (a different course)
An introduction to programming and the power of abstraction, using Abelson and Sussman's classic textbook of the same name. Key concepts include: building abstractions, computational processes, higher-order procedures, compound data, data abstractions, controlling interactions, generic operations, self-describing data, message passing, streams and infinite data structures, meta-linguistic abstraction, interpretation of programming languages, machine model, compilation, and embedded languages.


Structure and Interpretation of Computer Programs (a different course)
The CS 61 series is an introduction to computer science, with particular emphasis on software and on machines from a programmer's point of view. This first course concentrates mostly on the idea of abstraction, allowing the programmer to think in terms appropriate to the problem rather than in low-level operations dictated by the computer hardware. The next course, CS 61B, will deal with the more advanced engineering aspects of software on constructing and analyzing large programs and on techniques for handling computationally expensive programs. Finally, CS 61C concentrates on machines and how they carry out the programs you write.
In CS 61A, we are interested in teaching you about programming, not about any particular programming language. We consider a series of techniques for controlling program complexity, such as functional programming, data abstraction, object-oriented programming, and query systems. To get past generalities you must have programming practice in some particular language, and in this course we use Scheme, a dialect of Lisp. This language is particularly well-suited to the organizing ideas we want to teach. Our hope, however, is that once you have learned the essence of programming, you will find that picking up a new programming language is but a few days' work.


Data Structures
The CS 61 series is an introduction to computer science, with particular emphasis on software and on machines from a programmer’s point of view. CS 61A covered high-level approaches to problem-solving, providing you with a variety of ways to organize solutions to programming problems: as compositions of functions, collections of objects, or sets of rules. In CS 61B, we move to a somewhat more detailed (and to some extent, more basic) level of programming. As in 61A, the correctness of a program is important. In CS 61B, we’re concerned also with engineering. An engineer, it is said, is someone who can do for a dime what any fool can do for a dollar. Much of 61B will be concerned with the tradeoffs in time and memory for a variety of methods for structuring data. We’ll also be concerned with the engineering knowledge and skills needed to build and maintain moderately large programs.


Machine Structures
 The subjects covered in this course include C and assembly language programming, how higher level programs are translated into machine language, the general structure of computers, interrupts, caches, address translation, CPU design, and related topics. The only prerequisite is that you have taken Computer Science 61B, or at least have solid experience with a C-related programming language.


Programming Languages
Goals: Successful course participants will:
• Master universal programming-language concepts (including datatypes, functions, continuations, threads,
macros, types, objects, and classes) such that they can recognize them in strange guises.
• Learn to evaluate the power, elegance, and definition of programming languages and their constructs
• Attain reasonable proficiency programming in a functional style
• Find relevant literature somewhat more approachable.


Principles of Software Engineering
Study of major developments in software engineering over the past three decades. Topics may include design (information hiding, layering, open implementations), requirements specification (informal and formal approaches), quality assurance (testing, verification and analysis, inspections), reverse and re-engineering (tools, models, approaches).


Object Oriented Program Design
The concepts of the Object-oriented paradigm using Java. The basic principles of software engineering are emphasized. We study how to design and think in an object oriented fashion.


Algorithms
The design and analysis of algorithms is studied. Methodologies include: divide and conquer, dynamic programming, and greedy strategies. Their applications involve: sorting, ordering and searching, graph algorithms, geometric algorithms, mathematical (number theory, algebra and linear algebra) algorithms, and string matching algorithms.

We study algorithm analysis - worst case, average case, and amortized, with an emphasis on the close connection between the time complexity of an algorithm and the underlying data structures. We study NP-Completeness and methods of coping with intractability. Techniques such as approximation and probabilistic algorithms are studied for handling the NP-Complete problems.


Introduction to Algorithms
This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics covered include: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; amortized analysis; graph algorithms; shortest paths; network flow; computational geometry; number-theoretic algorithms; polynomial and matrix calculations; caching; and parallel computing.


Systems
Topics on the engineering of computer software and hardware systems: techniques for controlling complexity, system infrastructure, networks and distributed systems, atomicity and coordination of parallel activities, recovery and reliability, privacy of information, impact of computer systems on society. Case studies of working systems and outside reading in the current literature provide comparisons and contrasts.


Computer System Engineering
This course covers topics on the engineering of computer software and hardware systems: techniques for controlling complexity; strong modularity using client-server design, virtual memory, and threads; networks; atomicity and coordination of parallel activities; recovery and reliability; privacy, security, and encryption; and impact of computer systems on society. We will also look at case studies of working systems and readings from the current literature provide comparisons and contrasts, and do two design projects.


Graduate Computer Architecture
This course focuses on the techniques of quantitative analysis and evaluation of modern computing systems, such as the selection of appropriate benchmarks to reveal and compare the performance of alternative design choices in system design. The emphasis is on the major component subsystems of high performance computers: pipelining, instruction level parallelism, memory hierarchies, input/output, and network-oriented interconnections.


Computer Architecture
The purpose of this course is to give you a broad understanding of the concepts behind several advanced microarchitectural features in today’s microprocessors and to illustrate those concepts with appropriate (usually modern) machine examples. We will cover the rationale for and the designs of strategies for instruction sets, dynamic branch prediction, multiple-instruction issue, dynamic (out-of-order) instruction scheduling, multithreaded processors, shared memory multiprocessors, and, if there is time, dataflow machines. Some of these topics require some understanding from what is normally thought of as undergraduate material; for these, we’ll briefly review that material, and then go on from there.

You will augment your knowledge of the architectural schemes by doing experimental studies that examine and compare the performance of several alternative implementations for a particular feature. Here you will learn how to design architectural experiments, how to choose metrics that best illustrate a feature’s performance, how to analyze performance data and how to write up your experiment and results - all skills computer architects, and, actually, researchers and developers in any applied subfield of computer science, use on a regular basis.


Operating Systems and System Programming
The purpose of this course is to teach the design of operating systems and other systems. Topics we will cover include concepts of operating systems and systems programming; utility programs, subsystems, multiple-program systems; processes, interprocess communication, and synchronization; memory allocation, segmentation, paging; loading and linking, libraries; resource allocation, scheduling, performance evaluation; I/O systems, storage devices, file systems; basic networking, protocols, and distributed file systems, protection, security, and privacy.


How Computers Work
Includes the basics of digital logical design, computer organization and architecture including assembly language, processor design, memory hierarchies and pipelining. Students examine the detailed construction of a very simple computer. A higher level view of a modern RISC architecture is studied, using the Patterson and Hennessey introductory text, from both the programmer's point of view and the hardware designer's point of view. The distinction between RISC and CISC architectures is emphasized.


Performance Analysis
This course is intended to provide a broad introduction to computer system performance evaluation techniques and their application. Approaches considered include measurement/benchmarking, stochastic and trace driven simulation, stochastic queueing networks, and timed Petri


Database Management Systems
A more formal approach to Relational Database Management Systems, compared the way they were covered during Web Applications. Database systems are discussed from the physical layer of B-trees and file servers to the abstract layer of relational design. Also includes alternative and generic approaches to database design and database management system including relational, object-relational, and object-oriented systems, SQL standards, algebraic query languages, integrity constraints, triggers, functional dependencies, and normal forms. Other topics include tuning database transactions, security from the application perspective, and data warehousing.


Database Management Systems
Databases are at the heart of modern commercial application development. Their use extends beyond this to many applications and environments where large amounts of data must be stored for efficient update and retrieval. The purpose of this course is to provide an introduction to the design and use of database systems, as well as an appreciation of the key issues in building such systems, and working with multiple database systems.
We begin by covering basis aspcts of SQL, and illustrating several data management concepts through SQL features (e.g., views, constraints and triggers). Next, we study conceptual database design and normalization theory. We then study management of XML data, and cover the XPath and XQuery languages. We consider the issues arising in data integration from multiple databases, and more generally, issues in managing meta-data. Finally, we cover the basic aspects of the internals of database systems.


Transaction Processing for E-Commerce
Course covers Database Concurrency Control, Database Recovery, Basic Application Servers, Two-Phase Commit, Queuing, Replication, Application Servers.


Practical Aspects of Modern Cryptography
Course covers Symmetric Key Ciphers and Hashes, Public Key Ciphers, Analysis of Block Ciphers, AES and Attacks on Cryptographic Hashes, Certificates, Trust & PKI, Public Key Cryptography, Digital Rights Management, The Politics of Cryptography


Theory of Computation
A theoretical treatment of what can be computed and how fast it can be don. Applications to compilers, string searching, and control circuit design will be discussed. The hierarchy of finite state machines, pushdown machines, context free grammars and Turing machines will be analyzed, along with their variations. The notions of decidability, complexity theory and a complete discussion of NP-Complete problems round out the course.


Artificial Intelligence (4 lectures)
An quick overview of AI from both the technical and the philosophical points of view. Topics discussed include search, A*, Knowledge Representation, Neural Nets.


Applications of Artificial Intelligence
Introduction to the use of Artificial Intelligence tools and techniques in industrial and company settings. Topics include: foundations (search, knowledge representation) and tools such as expert systems, natural language interfaces and machine learning techniques.



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posted by Peteris Krumins at 4:01 PM | 116 comments

Thursday, June 22, 2006

More Physics Video Courses

How Things Work
For non-science majors: a practical introduction to physics and science in everyday life. This course considers objects from our daily environment and focuses on their principles of operation, histories, and relationships to one another. The emphasis for Physics 105 is on mechanical and thermal objects.

The course covers laws of motion, fluids, fluids and motion, heat and thermodynamics, phase transitions and resonance and mechanical waves.

I haven't watched this course because it is too basic for me and I know this stuff in detail.


The Mechanical Universe and Beyond
  • Video Lectures (University of California, 1985) (requires registration)
This series helps teachers demystify physics by showing students what it looks like. Field trips to hot-air balloon events, symphony concerts, bicycle shops, and other locales make complex concepts more accessible. Inventive computer graphics illustrate abstract concepts such as time, force, and capacitance, while historical reenactments of the studies of Newton, Leibniz, Maxwell, and others trace the evolution of theories. The Mechanical Universe helps meet different students' needs, from the basic requirements of liberal arts students to the rigorous demands of science and engineering majors. This series is also valuable for teacher professional development.

I own a DVD of these lectures (you can buy it) and have watched just a few of these lectures.
These lectures note historical events of physics and try to imitate atmosphere at the time certain discoveries were made.


The Wonders of Physics
Never has there been a time when an understanding of science has been more important to the well-being of individuals and to the nation than the present. Yet many recent studies have documented a lack of interest in science and hence a decline in science literacy in the United States.

To address this problem, the University of Wisconsin - Madison in 1984 began a program called The Wonders of Physics aimed at generating interest in physics among people of all ages and backgrounds. The heart of the program is a fast-paced presentation of physics demonstrations carefully chosen to be entertaining as well as educational.


Elementary College Physics

These are videos taken of introductory physics course, which was taught in the summer of 2005 at the University of North Carolina Wilmington.
This course covers basically the same material as MIT's 8.01 physics course.


Exploring Black Holes: General Relativity and Astrophysics.
Study of physical effects in the vicinity of a black hole as a basis for understanding general relativity, astrophysics, and elements of cosmology. Extension to current developments in theory and observation. Energy and momentum in flat spacetime; the metric; curvature of spacetime near rotating and nonrotating centers of attraction; trajectories and orbits of particles and light; elementary models of the Cosmos. Weekly meetings include an evening seminar and recitation. The last third of the semester is reserved for collaborative research projects on topics such as the Global Positioning System, solar system tests of relativity, descending into a black hole, gravitational lensing, gravitational waves, Gravity Probe B, and more advanced models of the Cosmos.


I have still many links other physics video links in my bookmarks. Will publish later.


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posted by Peteris Krumins at 5:10 PM | 3 comments

Free Mathematics Video Courses

The lectures are ordered by their complexity and background needed to understand them.


Discrete Mathematics:
This course covered the mathematical topics most directly related to computer science. Topics included: logic, relations, functions, basic set theory, countability and counting arguments, proof techniques, mathematical induction, graph theory, combinatorics, discrete probability, recursion, recurrence relations, and number theory. Emphasis will be placed on providing a context for the application of the mathematics within computer science. The analysis of algorithms requires the ability to count the number of operations in an algorithm. Recursive algorithms in particular depend on the solution to a recurrence equation, and a proof of correctness by mathematical induction. The design of a digital circuit requires the knowledge of Boolean algebra. Software engineering uses sets, graphs, trees and other data structures. Number theory is at the heart of secure messaging systems and cryptography. Logic is used in AI research in theorem proving and in database query systems. Proofs by induction and the more general notions of mathematical proof are ubiquitous in theory of computation, compiler design and formal grammars. Probabilistic notions crop up in architectural trade-offs in hardware design.


Algebra
  • Video Lectures (Click on the titles of lectures (they dont appear as links, but on click they work as links). Access to lectures restricted to USA only.
In this series, host Sol Garfunkel explains how algebra is used for solving real-world problems and clearly explains concepts that may baffle many students. Graphic illustrations and on-location examples help students connect mathematics to daily life. The series also has applications in geometry and calculus instruction. Algebra is also valuable for teachers seeking to review the subject matter.


Linear Algebra
This is a basic subject on matrix theory and linear algebra. Emphasis is given to topics that will be useful in other disciplines, including systems of equations, vector spaces, determinants, eigenvalues, similarity, and positive definite matrices.


Mathematical Problems II
Mathematics originated in the distant past as our ancestors tried to understand the world around them.

First, the course will survey the role that problems and problem-solving have played in the historical development of mathematics.

In Lecture 1 course covers Mesopotomian and Egyptian mathematics

Then the course goes over the basic elements of problem solving:
Models, Abstraction, Conjectures, Hypotheses, Proofs (Heuristic, Rigorous), Generalizations


Differential Equations

Differential Equations are the language in which the laws of nature are expressed. Understanding properties of solutions of differential equations is fundamental to much of contemporary science and engineering. Ordinary differential equations (ODE's) deal with functions of one variable, which can often be thought of as time. Topics include: Solution of first-order ODE's by analytical, graphical and numerical methods; Linear ODE's, especially second order with constant coefficients; Undetermined coefficients and variation of parameters; Sinusoidal and exponential signals: oscillations, damping, resonance; Complex numbers and exponentials; Fourier series, periodic solutions; Delta functions, convolution, and Laplace transform methods; Matrix and first order linear systems: eigenvalues and eigenvectors; and Non-linear autonomous systems: critical point analysis and phase plane diagrams.


Mathematical Methods for Engineers I
This course provides a review of linear algebra, including applications to networks, structures, and estimation, Lagrange multipliers. Also covered are: differential equations of equilibrium; Laplace's equation and potential flow; boundary-value problems; minimum principles and calculus of variations; Fourier series; discrete Fourier transform; convolution; and applications.


Have fun watching these. I have approx. 40 more links of math video lectures to sort.


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posted by Peteris Krumins at 5:04 PM | 5 comments

Monday, June 19, 2006

Free Physics Video and Audio Courses

In all my posts if I have multiple items to post, I will categorize them based on their difficulty.


Descriptive introduction to physics:
No prior physics is required. Moreover, even if you are a physics major, you will find that most of the material is new. Physics majors spend so much time learning the math and to abstract calculations that they often do not get to the important results. This course is now open for physics majors too, in fact, is is an excellent supplement for your other physics courses.


Classical Mechanics:
In addition to the basic concepts of Newtonian Mechanics, Fluid Mechanics, and Kinetic Gas Theory, a variety of interesting topics are covered in this course: Binary Stars, Neutron Stars, Black Holes, Resonance Phenomena, Musical Instruments, Stellar Collapse, Supernovae, Astronomical observations from very high flying balloons (lecture #35), and you will be allowed a peek into the intriguing Quantum World.


Introductory Physics
Introduction to forces, kinetics, equilibria, fluids, waves, and heat. This course presents concepts and methodologies for understanding physical phenomena, and is particularly useful preparation for upper division study in biology and architecture.


Electricity and Magnetism:
In addition to the basic concepts of Electromagnetism, a vast variety of interesting topics are covered in this course: Lightning, Pacemakers, Electric Shock Treatment, Electrocardiograms, Metal Detectors, Musical Instruments, Magnetic Levitation, Bullet Trains, Electric Motors, Radios, TV, Car Coils, Superconductivity, Aurora Borealis, Rainbows, Radio Telescopes, Interferometers, Particle Accelerators (a.k.a. Atom Smashers or Colliders), Mass Spectrometers, Red Sunsets, Blue Skies, Haloes around Sun and Moon, Color Perception, Doppler Effect, Big-Bang Cosmology.


Vibrations and Waves:
In addition to the traditional topics of mechanical vibrations and waves, coupled oscillators, and electro-magnetic radiation, students will also learn about musical instruments, red sunsets, glories, coronae, rainbows, haloes, X-ray binaries, neutron stars, black holes and big-bang cosmology.


Symmetry, Structure, and Tensor Properties of Materials
This course covers the derivation of symmetry theory; lattices, point groups, space groups, and their properties; use of symmetry in tensor representation of crystal properties, including anisotropy and representation surfaces; and applications to piezoelectricity and elasticity.

I will post other links in a few days.


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posted by Peteris Krumins at 10:45 AM | 8 comments

Video Lectures

Welcome to my free science resource blog.

It is great that some of the top universities have published video recordings of their lectures online. Quoting professor Walter Lewin from MIT "knowledge only adds, it never subtracts".
This is true and I can't agree more. The video lectures ease perception of material enormously.

I have watched at least five video courses during last year in physics, mathematics and computer science. So I will be focusing mostly on lectures in these subjects.

A little about me.
I am physics student and I am very interested in physics so I have spent quite a while searching for all available video lectures in physics.

It is essential that a physicist knows mathematics perfectly so I have also collected links to lectures on mathematics.

One of the reasons I chose to study physics is because I was proficient at computer science and studying it would be a waste of time since I knew 80% of what is taught at university.
I have also a good collection of video lectures in computer science.

I am not interested much in other sciences so mathematics, physics and computer science is what I will be focusing on.

I will gradually publish all my findings here. I have lots of links to go through.

posted by Peteris Krumins at 10:18 AM | 11 comments