Online and Remote Learning

In this course, you’ll learn how DevOps tools and applications help technology leaders deliver software products with greater agility. You’ll explore the eight stages of the DevOps tool chain—Plan, Code, Build, Test, Release, Deployment, Operations and Monitoring—and get hands-on experience using a range of agnostic tools and platforms. You’ll learn the benefits and challenges of using cloud-specific platforms such as AWS, Azure and GCP and gain valuable tools and experience that can enhance your position within your organization. By the end of this course, you'll be able to: Define the basic concepts of DevOps  Describe the eight different phases of DevOps – Plan, Code, Build, Test, Release, Deployment, Operations, and Monitoring, with benefits Evaluate and apply the eight phases of DevOps through labs and demonstrations.  Analyze DevOps Cloud Offerings for AWS, Azure and GCP Describe advanced concepts of DevOps such as DevSecOps, DataOps, MLOps, AIOps related to Security and Compliance

Self-driving laboratories (SDLs) incorporate AI and automation into scientific laboratories to speed up the discovery of new materials for applications such as clean energy and cancer drugs. Discover the essential principles of SDLs by building a ‘Hello World’ SDL from scratch. In this asynchronous, remote course, you will build a self-driving colour matcher using dimmable LEDs and a light sensor. This introduction will help you implement hardware/software communication, database integration, microcontroller programming, and Bayesian optimization. Each of these are important components of an SDL, and you will get a taste of these in the course modules that will prepare you for deeper dives in future courses. This course is presented in partnership with the Acceleration Consortium at the University of Toronto. This is an online, self-directed course, and you can work through the modules at your own pace. You can expect to complete the course in a month, but have up to 1 year to complete it. Within 4-6 weeks of successfully completing this course, you will receive your micro-credential indicating achievement of the outlined learning outcomes and competencies/skills. Micro-credentials are tamper-proof, verifiable, blockchain-based, and 100% digital. They can be shared on social media, including LinkedIn and Facebook, embedded in websites or downloaded as PDFs. By the end of this course, you'll be able to: Define and explain key terms and principles of self-driving labs to demonstrate understanding Apply MQTT or similar frameworks to send commands and receive sensor data over WiFi Demonstrate the ability to use MongoDB to store and retrieve experiment configurations and results effectively Develop and implement software on a Raspberry Pi Pico W microcontroller to control device power and read sensor data accurately Modify a Bayesian optimization script using the Ax Platform to iteratively propose new experimental configurations Integrate the individual SDL components to orchestrate the full ‘Hello World’ workflow Competencies/skills developed in this micro course include: Basic self-driving lab literacy Microcontrollers and sensors Bayesian optimization Hardware/software communication Database management Workflow orchestration

If you want to make films but lack the track record to attract major funding, this course is for you. You’ll learn how to produce a film, from writing through distribution, on a budget under $250,000. You’ll break down a script, create efficient schedules, calculate appropriate tax credits, and get tips on working with union crews to run a smooth shoot. You’ll tackle post-production, draft a marketing plan, and learn how to pitch your project to producers, broadcasters, distributors, and other funding agencies. Adapt a script to work within the micro-budget world and breakdown a script; Execute applications for arts grants and other Government funding agencies; develop and execute a crowdfunding campaign; and calculate CPTC and OFTTC tax credits; Create a budget and production schedule, run a smooth shoot (principal photography), and tackle post-production; Execute a marketing and distribution plan to create maximum exposure for your film; Create materials needed to pitch your projects to producers, broadcasters, distributors, and other funding agencies.

This course is designed for students who have completed SCS Japanese Level VI or have equivalent language skills. The course uses texts at an intermediate level (B1 on the CEFR grid) and provides more opportunities for oral practice. You will be introduced to expressions for remarking on things you notice, offering conjectures, reporting information, and making comments. In this way, you will gain the skills to initiate conversations about things or events you come across in daily life. You will be able to convey a variety of meanings using appropriate conjunctions, particles and more sophisticated sentence endings. To determine your Japanese language level, please take a moment to complete our Japanese Placement Exercise before registering. •  Learn about trends and issues in contemporary Japanese society and the Japanese culture and customs related to these trends and issues. •  Express what you have noticed and observed at home, at work, and out and about, including trends and changes. •  Develop conversations by sharing information you gained from other sources or by asking people to think along with you on questions that concern you. •  Gain vocabulary necessary for social trends and environmental issues such as food and health. •  Be able to read and write 160-200 basic Kanji characters.  

No prior knowledge of Farsi is needed to take this beginners course. It uses intensive class participation to teach you everyday interactions by focusing on phonetics, the spoken word and simple grammar. Whether for professional or personal reasons, you'll be able to greet people, request and give information about your immediate surroundings, express simple likes and dislikes and describe where you live and people you know. Learn more about Farsi heritage and Central Asian and Indian history. Pronounce Farsi clearly. Begin to use appropriate grammar, syntax and vocabulary in simple everyday situations. Form simple sentences in Farsi about yourself and your family.

With business-to-business (B2B) sales now outpacing sales to consumers, organizations need people who can craft dynamic, data-driven B2B strategies that drive growth and achieve revenue goals. In this course, you will learn to develop customer-focused content that aligns to marketing strategies and use multiple indicators to measure and evaluate the business impact of your efforts. You will explore key tactics that modern B2B marketers leverage across the buyer’s journey and learn how to collaborate with sales teams to satisfy shifting buyer demands. By the end of this course, you'll be able to: Design a data driven B2B marketing strategy that achieves revenue goals and drives business growth Understand key tactics that modern B2B marketers leverage across the buyer’s journey Practice effective techniques to build strong relationships with sales teams, emphasizing the critical role of collaboration and communication in achieving B2B marketing success Develop content that is customer centric, educational, and aligns to your marketing strategy Measure and evaluate the business impact of your marketing efforts, using both leading and lagging indicators

Accelerate your career in data management with this overview course designed to help you align digital assets with organizational strategy. You’ll learn the basics of data architecture, management, and governance and master the vocabulary used to design, execute, and communicate data strategy effectively. You’ll acquire tools and skills to manage data responsibly and emerge ready to manage data assets through the lifecycle and take on larger, more strategic projects. By the end of this course, you'll be able to: Define guiding principles and best practices for data management and how these can be applied to functional areas and roles of data management.  Explain how data modeling, storage, data mapping and lifecycle management allow organizations to best structure and store data with consistent processes.  Discuss how integration and interoperability can be used to maintain privacy and confidentiality.  Apply techniques related to master data, reference data, and metadata to utilize and organize different versions of data and descriptions of the data.  Apply the foundations of data warehousing and business intelligence and analyze how staging and storing data can be used to present useful organizational insights. Explain how data quality and controls help an organization ensure that the data assets retain the highest quality and accuracy. Consider different data governance and security policies to provide ownership and oversight for an organization to manage data as an asset in a sustainable manner.

Workforces facing change and uncertainty need psychologically safe leaders who promote learning, inclusion, and collaboration. This course will prepare you to be that leader. You’ll learn how to master thoughts and emotions, reduce reactivity, improve focus and concentration, and renew energy levels to prevent burnout. You’ll explore the root causes of anxiety and depression and learn how to prevent clinical-level symptoms. You’ll draw on the science of consciousness, cognitive science, and neurobiology to create optimal conditions for solving complex challenges. By the end of this course, you'll be able to: Understand the nature of the mind and neuroplasticity Examine thoughts and emotions, adopt a growth mindset and process-orientation Utilize techniques to systematically renew energy levels to prevent burnout Recognize psychological safety and how it affects learning and innovation Cultivate authenticity and uncover unique talents, strengths, and values in self and others Improve collaboration and foster a sense of belonging and purpose

*NEW SHORTENED FORMAT* If you want to learn about the structure of the human body, this intensive, 16-week online human anatomy course could be for you. Included are 17 hour-long video lectures from award-winning professors in the Faculty of Medicine, each covering a different lesson in human anatomy, including examples of medical applications. Assigned readings and problem-solving exercises will deepen your understanding of the human body, from tissues to the body wall and its contained organs, to the structure of our head, neck and limbs. You’ll emerge with a greater appreciation of human anatomy, its complex relationships, and basic clinical applications. Course Details: The course is taught by Faculty members in the Department of Surgery in the Faculty of Medicine at the University of Toronto and is administered through the University’s School of Continuing Studies. It consists of 17 video lectures of approximately 1hour. The course is divided into 2 units. Each unit contains a number of modules. Each module is followed by a multiple-choice quiz designed to provide a pause for you to consolidate and reflect on the information. By the end of this course, you'll be able to: Understand the structure and function of the various tissue types that make up the human body. Explore the structure of the body wall and the organs contained within its cavities, including those of the nervous, respiratory, cardiovascular, digestive, urinary, and reproductive systems.

Deep Reinforcement Learning covers how to construct an intelligent agent that learns by interacting with its environment.  It builds on the introduction to reinforcement learning and deep learning provided in the Intelligent Agents and Deep Learning AI certificate courses, demonstrating how to combine these two powerful technologies to develop agents that can learn to perform at superhuman levels and continue to improve with experience.  The course illustrates how many of the groundbreaking new systems from DeepMind and other AI companies work. By the end of this course, you'll be able to: Explore the fundamental principles of deep reinforcement learning, including dynamic programming, value functions and rewards. Learn to use modern Deep Reinforcement Learning tools and libraries such as TorchRL. Apply a range of advanced techniques, including Dynamic Programming, Monte Carlo Methods, Deep Q Networks, Policy Gradient Methods, and Actor-Critic Methods, to construct intelligent agents. Recognize challenges in combining deep learning with reinforcement learning and employ strategies to mitigate issues that arise. Apply Deep Reinforcement Learning in multi-agent settings, including cooperative, competitive, and mixed games. Explore recent advances and emerging research in Deep Reinforcement Learning to remain at the forefront of the field.