23 Things is a suite of 23 self-paced online modules that cover a range of topics from video editing to basic coding. Each module or 'thing' consists of information, interactive activities, and invitations to try out various open and free software applications and technologies. The modules have been created using H5P and can be downloaded individually as a single H5P file, modified and re-used under a CC-BY-SA license - simply click on the 'reuse' link at the bottom of each module.

The content was created by Curtin University students as part of a 'students as partners' project.

" This is a graduate course on the design and analysis of algorithms, covering several advanced topics not studied in typical introductory courses on algorithms. It is especially designed for doctoral students interested in theoretical computer science."

Following a brief classroom discussion of relevant principles, each student completes the paper design of several advanced circuits such as multiplexers, sample-and-holds, gain-controlled amplifiers, analog multipliers, digital-to-analog or analog-to-digital converters, and power amplifiers. One of each student's designs is presented to the class, and one may be built and evaluated. Associated laboratory emphasizing the use of modern analog building blocks. Alternate years.

Recent results in cryptography and interactive proofs. Lectures by instructor, invited speakers, and students. Alternate years. The topics covered in this course include interactive proofs, zero-knowledge proofs, zero-knowledge proofs of knowledge, non-interactive zero-knowledge proofs, secure protocols, two-party secure computation, multiparty secure computation, and chosen-ciphertext security.

" This course covers concepts and techniques for the design and implementation of large software systems that can be adapted to uses not anticipated by the designer. Applications include compilers, computer-algebra systems, deductive systems, and some artificial intelligence applications. Topics include combinators, generic operations, pattern matching, pattern-directed invocation, rule systems, backtracking, dependencies, indeterminacy, memoization, constraint propagation, and incremental refinement. Substantial weekly programming Assignments and Labs are an integral part of the subject. There will be extensive programming Assignments and Labs, using MIT/GNU Scheme. Students should have significant programming experience in Scheme, Common Lisp, Haskell, CAML or some other "functional" language."

Building on Complex Adaptive Systems theory and basic Agent Based Modeling knowledge presented in SPM4530, the Advanced course will focus on the model development process. The students are expected to conceptualize, develop and verify a model during the course, individually or in a group. The modeling tasks will be, as much as possible, based on real life research problems, formulated by various research groups from within and outside the faculty.
Study Goals The main goal of the course is to learn how to form a modeling question, perform a system decomposition, conceptualize and formalize the system elements, implement and verify the simulation and validate an Agent Based Model of a socio-technical system.

This is a textbook for first year Computer Science. Algorithms and Data Structures With Applications to Graphics and Geometry.

In-depth study of an active research topic in computer graphics. Topics change each term. Readings from the literature, student presentations, short assignments, and a programming project. Animation is a compelling and effective form of expression; it engages viewers and makes difficult concepts easier to grasp. Today's animation industry creates films, special effects, and games with stunning visual detail and quality. This graduate class will investigate the algorithms that make these animations possible: keyframing, inverse kinematics, physical simulation, optimization, optimal control, motion capture, and data-driven methods. Our study will also reveal the shortcomings of these sophisticated tools. The students will propose improvements and explore new methods for computer animation in semester-long research projects. The course should appeal to both students with general interest in computer graphics and students interested in new applications of machine learning, robotics, biomechanics, physics, applied mathematics and scientific computing.

This course will provide an overview of a new vision for Human-Computer Interaction (HCI) in which people are surrounded by intelligent and intuitive interfaces embedded in the everyday objects around them. It will focus on understanding enabling technologies and studying applications and experiments, and, to a lesser extent, it will address the socio-cultural impact. Students will read and discuss the most relevant articles in related areas: smart environments, smart networked objects, augmented and mixed realities, ubiquitous computing, pervasive computing, tangible computing, intelligent interfaces and wearable computing. Finally, they will be asked to come up with new ideas and start innovative projects in this area.

An introduction to the main techniques of Artifical Intelligence: state-space search methods, semantic networks, theorem-proving and production rule systems. Important applications of these techniques are presented. Students are expected to write programs exemplifying some of techniques taught, using the LISP lanuage.

This course introduces students to the basic knowledge representation, problem solving, and learning methods of artificial intelligence. Upon completion of 6.034, students should be able to develop intelligent systems by assembling solutions to concrete computational problems, understand the role of knowledge representation, problem solving, and learning in intelligent-system engineering, and appreciate the role of problem solving, vision, and language in understanding human intelligence from a computational perspective.

This course provides a challenging introduction to some of the central ideas of theoretical computer science. Beginning in antiquity, the course will progress through finite automata, circuits and decision trees, Turing machines and computability, efficient algorithms and reducibility, the P versus NP problem, NP-completeness, the power of randomness, cryptography and one-way functions, computational learning theory, and quantum computing. It examines the classes of problems that can and cannot be solved by various kinds of machines. It tries to explain the key differences between computational models that affect their power.

If you've ever spent hours renaming files or updating hundreds of spreadsheet cells, you know how tedious tasks like these can be. But what if you could have your computer do them for you?

In Automate the Boring Stuff with Python, you'll learn how to use Python to write programs that do in minutes what would take you hours to do by hand-no prior programming experience required. Once you've mastered the basics of programming, you'll create Python programs that effortlessly perform useful and impressive feats of automation to:

Search for text in a file or across multiple files
Create, update, move, and rename files and folders
Search the Web and download online content
Update and format data in Excel spreadsheets of any size
Split, merge, watermark, and encrypt PDFs
Send reminder emails and text notifications
Fill out online forms

Step-by-step instructions walk you through each program, and practice projects at the end of each chapter challenge you to improve those programs and use your newfound skills to automate similar tasks.

Don't spend your time doing work a well-trained monkey could do. Even if you've never written a line of code, you can make your computer do the grunt work. Learn how in Automate the Boring Stuff with Python.

Graduate-level introduction to automatic speech recognition. Provides relevant background in acoustic theory of speech production, properties of speech sounds, signal representation, acoustic modeling, pattern classification, search algorithms, stochastic modeling techniques (including hidden Markov modeling), and language modeling. Examines approaches of state-of-the-art speech recognition systems. Introduces students to the rapidly developing field of automatic speech recognition. Its content is divided into three parts. Part I deals with background material in the acoustic theory of speech production, acoustic-phonetics, and signal representation. Part II describes algorithmic aspects of speech recognition systems including pattern classification, search algorithms, stochastic modelling, and language modelling techniques. Part III compares and contrasts the various approaches to speech recognition, and describes advanced techniques used for acoustic-phonetic modelling, robust speech recognition, speaker adaptation, processing paralinguistic information, speech understanding, and multimodal processing.

Study of an area of current interest in theoretical computer science. Topic varies from term to term. This course is a study of Behavior of Algorithms and covers an area of current interest in theoretical computer science. The topics vary from term to term. During this term, we discuss rigorous approaches to explaining the typical performance of algorithms with a focus on the following approaches: smoothed analysis, condition numbers/parametric analysis, and subclassing inputs.

While big data infiltrates all walks of life, most firms have not changed sufficiently to meet the challenges that come with it. In this course, you will learn how to develop a big data strategy, transform your business model and your organization.

This course will enable professionals to take their organization and their own career to the next level, regardless of their background and position.

Professionals will learn how to be in charge of big data instead of being subject to it. In particular, they will become familiar with tools to:

assess their current situation regarding potential big data-induced changes of a disruptive nature,
identify their options for successfully integrating big data in their strategy, business model and organization, or if not possible, how to exit quickly with as little loss as possible, and
strengthen their own position and that of their organization in our digitalized knowledge economy
The course will build on the concepts of product life cycles, the business model canvas, organizational theory and digitalized management jobs (such as Chief Digital Officer or Chief Informatics Officer) to help you find the best way to deal with and benefit from big data induced changes.

Blender 3D: Noob to Pro is a product of shared effort by numerous team members and anonymous editors. Its purpose is to teach people how to create three-dimensional computer graphics using Blender, a free software application. This book is intended to be used in conjunction with other on-line resources that complement it.

"A Byte of Python" is a free book on programming using the Python language. It serves as a tutorial or guide to the Python language for a beginner audience. If all you know about computers is how to save text files, then this is the book for you. There are many translations of the book available in different human languages.

C is the most commonly used programming language for writing operating systems. The first operating system written in C is Unix. Later operating systems like GNU/Linux were all written in C. Not only is C the language of operating systems, it is the precursor and inspiration for almost all of the most popular high-level languages available today. In fact, Perl, PHP, Python and Ruby are all written in C. By way of analogy, let's say that you were going to be learning Spanish, Italian, French, or Portuguese. Do you think knowing Latin would be helpful? Just as Latin was the basis of all of those languages, knowing C will enable you to understand and appreciate an entire family of programming languages built upon the traditions of C. Knowledge of C enables freedom.

Although C# is derived from the C programming language, it introduces some unique and powerful features, such as delegates (which can be viewed as type-safe function pointers) and lambda expressions which introduce elements of functional programming languages, as well as a simpler single class inheritance model (than C++) and, for those of you with experience in "C-like" languages, a very familiar syntax that may help beginners become proficient faster than its predecessors. Similar to Java, it is object-oriented, comes with an extensive class library, and supports exception handling, multiple types of polymorphism, and separation of interfaces from implementations. Those features, combined with its powerful development tools, multi-platform support, and generics, make C# a good choice for many types of software development projects: rapid application development projects, projects implemented by individuals or large or small teams, Internet applications, and projects with strict reliability requirements. Testing frameworks such as NUnit make C# amenable to test-driven development and thus a good language for use with Extreme Programming (XP). Its strong typing helps to prevent many programming errors that are common in weakly typed languages.