This course can also be taken for academic credit as ECEA 5315, part of CU Boulder’s Master of Science in Electrical Engineering degree. Course Description: In this course, students will design and build a microprocessor-based embedded system application using a real-time operating system or RT POSIX extensions with Embedded Linux. The course focus is on the process as well as fundamentals of integrating microprocessor-based embedded system elements for digital command and control of typical embedded hardware systems. Lab Description: The course requires the student to install embedded Linux on the Raspberry Pi ARM A-Series System-on-Chip processor. This course must be completed using a Raspberry Pi as an embedded system (headless) not a PC running Linux. You will however find Linux as a useful host development system or Windows with an SSH terminal access tool such as Putty, MobaXterm, or equivalent.

Operations Research (OR) is a field in which people use mathematical and engineering methods to study optimization problems in Business and Management, Economics, Computer Science, Civil Engineering, Electrical Engineering, etc. The series of courses consists of three parts, we focus on deterministic optimization techniques, which is a major part of the field of OR. As the second part of the series, we study some efficient algorithms for solving linear programs, integer programs, and nonlinear programs. We also introduce the basic computer implementation of solving different programs, integer programs, and nonlinear programs and thus an example of algorithm application will be discussed.

In Course 4 of the Natural Language Processing Specialization, you will: a) Translate complete English sentences into German using an encoder-decoder attention model, b) Build a Transformer model to summarize text, c) Use T5 and BERT models to perform question-answering, and d) Build a chatbot using a Reformer model. By the end of this Specialization, you will have designed NLP applications that perform question-answering and sentiment analysis, created tools to translate languages and summarize text, and even built a chatbot! Learners should have a working knowledge of machine learning, intermediate Python including experience with a deep learning framework (e.g., TensorFlow, Keras), as well as proficiency in calculus, linear algebra, and statistics. Please make sure that you’ve completed course 3 - Natural Language Processing with Sequence Models - before starting this course. This Specialization is designed and taught by two experts in NLP, machine learning, and deep learning. Younes Bensouda Mourri is an Instructor of AI at Stanford University who also helped build the Deep Learning Specialization. Łukasz Kaiser is a Staff Research Scientist at Google Brain and the co-author of Tensorflow, the Tensor2Tensor and Trax libraries, and the Transformer paper.

The Capstone Project gives you an opportunity to revisit the concepts covered and develop a workable solution for the given problem statement using the best practices. The solution needs to be developed in accordance with the industry standards within the stipulated time and must be based on the guidelines provided.

Code and run your first Bash script in minutes without installing anything! This course is designed for learners with no scripting experience. Learners will gain hands-on practice on an Ubuntu system that can be easily transferred to other Unix-based operating systems. The modules in this course cover scripting basics (e.g. control structures), advanced scripting (e.g. regular expressions), git version control, and system configuration (e.g. installing and updating). To allow for a truly hands-on, self-paced learning experience, this course is video-free. Assignments contain short explanations with images and runnable script examples with suggested edits to explore script examples further, building a deeper understanding by doing. You'll benefit from instant feedback from a variety of assessment items along the way, gently progressing from quick understanding checks (multiple choice, fill in the blank, and un-scrambling code blocks) to small, approachable exercises that take minutes instead of hours.

We live in an age increasingly dominated by algorithms. As machine learning models begin making important decisions based on massive datasets, we need to be aware of their limitations in the real world. Whether it's making loan decisions or re-routing traffic, machine learning models need to accurately reflect our shared values. In this course, we will explore the rise of algorithms, from the most basic to the fully-autonomous, and discuss how to make them more ethically sound.

In this MOOC, you will learn the history of DDoS attacks and analyze new Mirai IoT Malware and perform source code analysis. you will be provided with a brief overview of DDoS Defense techniques. You learn an Autonomous Anti-DDoS Network called A2D2 for small/medium size organizations to deal with DDoS attacks. A2D2 uses Linux Firewall Rate limiting and Class Based Queueing, and subnet flood detection to handle various DDoS traffic types. You learn the new Intrusion tolerance paradigm with proxy-based multipath routing for DDoS defense. By developing and deploying such a new security mechanism, you can improve performance and reliability of the system at the same time and it does not have to be just an overhead. By the end of this course, you should be able to analyze new DDoS malware, collect forensic evidences, deploy firewall features to reduce the impact of DDoS on your system and develop strategies for dealing with future DDoS attacks. For the pre-requisites, we recommend the learners take the Design and Analyze Secure Networked Systems course to learn the basic security concepts and principles and take the Secure Networked System with Firewall and IDS courses to learn the basic firewall and IDS systems.

By the end of this project, you will be able to apply user centered design principles to design an iPhone application flow with custom wireframes with the goal of creating a seamless User Experience (UX). To design an iPhone application flow, you will gain hands-on experience applying design thinking, user interface knowledge, and context from each step of the customer journey in the Miro online visual collaboration platform for teamwork. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

This course builds upon the skills and coding practices learned in both Principles of Secure Coding and Identifying Security Vulnerabilities, courses one and two, in this specialization. This course uses the focusing technique that asks you to think about: “what to watch out for” and “where to look” to evaluate and ultimately remediate fragile C++ library code. The techniques you’ll be examining will make your programs perform accurately and be resistant to attempts to perform inaccurately. This is really what the term secure programming means. You will be shown common errors that people make, and then learn how to program more robustly. You will apply tips and best practices to help you improve your programming style and help you to avoid common problems like buffer overflows, which may or may not cause security problems.

Do you want to know how robots work? Are you interested in robotics as a career? Are you willing to invest the effort to learn fundamental mathematical modeling techniques that are used in all subfields of robotics? If so, then the "Modern Robotics: Mechanics, Planning, and Control" specialization may be for you. This specialization, consisting of six short courses, is serious preparation for serious students who hope to work in the field of robotics or to undertake advanced study. It is not a sampler. In Course 5 of the specialization, Robot Motion Planning and Wheeled Mobile Robots, we delve into advanced topics in robotics. Chapter 12, Grasping and Manipulation, of the "Modern Robotics" textbook covers the modeling of kinematics and forces between rigid bodies in contact, and applies the modeling to analysis and planning of robot grasping and other manipulation tasks. Chapter 13, Wheeled Mobile Robots, covers modeling, motion planning, and feedback control of omnidirectional and nonholonomic wheeled mobile robots, and concludes by addressing control of mobile manipulators consisting of a wheeled mobile base and a robot arm. This course follows the textbook "Modern Robotics: Mechanics, Planning, and Control" (Lynch and Park, Cambridge University Press 2017). You can purchase the book or use the free preprint pdf. You will build on a library of robotics software in the language of your choice (among Python, Mathematica, and MATLAB) and use the free cross-platform robot simulator V-REP, which allows you to work with state-of-the-art robots in the comfort of your own home and with zero financial investment.