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Teaches cybrary, which is associated with IT and cybersecurity, which are highly in-demand fields
Develops intermediate as well as professional level cybersecurity skills and knowledge
Offers a practical approach to learning cybersecurity
Provides hands-on labs and interactive materials
Takes a creative approach to an otherwise established topic, field, or subject
Requires that this course be taken in serial with others
Leads to CySA+ certification

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Start on the road to a Self-Driving Car career with these activities:
Review prerequisite math concepts
Strengthen foundational knowledge in mathematics, which is essential for success in the course.
Browse courses on Algebra
Show steps
  • Identify specific math concepts that are prerequisites for the course.
  • Review textbooks, online resources, or attend workshops to refresh your knowledge.
Read 'The 7 Habits of Highly Effective People'
Provide foundational principles for personal growth and effectiveness, complementing the course's focus on habit formation.
Show steps
  • Read the book and reflect on the key principles.
  • Identify areas in your life where you can apply the principles.
Read 'The Power of Habit'
Introduce key concepts related to habit formation, which will be directly applicable to the course material on behavior change.
Show steps
  • Read the book and take notes on key concepts.
  • Identify a habit you'd like to change and apply the principles from the book.
Five other activities
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Engage in online discussions
Foster collaboration and critical thinking by engaging with peers and discussing course concepts.
Show steps
  • Join online forums or discussion groups.
  • Post thoughtful questions and engage with others' perspectives.
  • Reflect on the discussions and apply insights to your understanding.
Complete coding challenges
Strengthen technical skills and problem-solving abilities through hands-on practice.
Browse courses on Python
Show steps
  • Identify online coding platforms or resources.
  • Choose challenges that align with course concepts.
  • Solve the challenges independently or seek assistance when needed.
  • Review solutions and analyze your approach.
Develop a blog post or article
Enhance comprehension and critical analysis by summarizing and explaining course concepts in your own words.
Show steps
  • Choose a topic related to the course material.
  • Research and gather information from credible sources.
  • Write a draft of your blog post or article, ensuring clarity and organization.
  • Edit and proofread your work.
  • Publish your blog post or article and share it with others.
Contribute to an open-source project
Gain practical experience in software development and contribute to the community while applying course concepts.
Show steps
  • Explore open-source projects related to the course material.
  • Identify an area where you can contribute.
  • Follow the project's guidelines and contribute code or documentation.
  • Engage with other contributors and seek feedback.
Design and implement a habit-tracking app
Apply course concepts to a practical project, reinforcing technical skills and understanding of habit formation.
Show steps
  • Define the scope and features of your app.
  • Design the user interface and develop the app's functionality.
  • Test the app and gather feedback for improvements.
  • Deploy the app to a platform and promote it to potential users.

Career center

Learners who complete Start on the road to a Self-Driving Car career will develop knowledge and skills that may be useful to these careers:
Project Manager
A Project Manager plans, executes, and controls the development of self-driving cars. This course can help build a foundation in the key principles of project management, including project planning, scope management, and risk management. Additionally, the course will cover topics such as Agile development, Scrum, and Kanban, which are essential for the project managers working on self-driving cars.
Data Scientist
A Data Scientist collects, analyzes, and interprets data to help improve the performance of self-driving cars. This course can help build a foundation in the key principles of data science, including statistics, machine learning, and data mining. Additionally, the course will cover topics such as data collection, data cleaning, and data visualization, which are essential for the data scientists working on self-driving cars.
Software Engineer
A Software Engineer designs, develops, and tests the software that runs self-driving cars. This course can help build a foundation in the key principles of software engineering, including object-oriented programming, data structures, and algorithms. Additionally, the course will cover topics such as embedded systems, real-time systems, and safety-critical systems, which are essential for the software of self-driving cars.
Product Manager
A Product Manager defines, plans, and executes the roadmap for self-driving cars. This course can help build a foundation in the key principles of product management, including product planning, market research, and user experience. Additionally, the course will cover topics such as lean product development, agile development, and design thinking, which are essential for the product managers working on self-driving cars.
Sales Engineer
A Sales Engineer sells and supports self-driving cars. This course can help build a foundation in the key principles of sales engineering, including technical sales, customer relationship management, and product demonstrations. Additionally, the course will cover topics such as self-driving car technology, market trends, and competitive analysis, which are essential for the sales engineers working on self-driving cars.
Controls Engineer
A Controls Engineer designs, develops, and tests the systems that control the movement of self-driving cars. This course can help build a foundation in the key principles of control engineering, including dynamics, kinematics, and feedback control. Additionally, the course will cover topics such as path planning, trajectory optimization, and vehicle dynamics, which are essential for the control systems of self-driving cars.
Perception Engineer
A Perception Engineer designs, develops, and tests systems that allow self-driving cars to 'see' and interpret their surroundings. This course can help build a foundation in the key principles of perception engineering, including computer vision, sensor fusion, and machine learning. Additionally, the course will cover topics such as object detection, tracking, and lane estimation, which are essential for the perception systems of self-driving cars.
Technical Writer
A Technical Writer documents the technical aspects of self-driving cars. This course can help build a foundation in the key principles of technical writing, including technical documentation, user guides, and white papers. Additionally, the course will cover topics such as self-driving car technology, industry standards, and writing for a technical audience, which are essential for the technical writers working on self-driving cars.
Safety Engineer
A Safety Engineer designs, develops, and implements safety features for self-driving cars. This course can help build a foundation in the key principles of safety engineering, including risk assessment, hazard analysis, and safety management. Additionally, the course will cover topics such as self-driving car technology, industry standards, and accident investigation, which are essential for the safety engineers working on self-driving cars.
Quality Assurance Engineer
A Quality Assurance Engineer tests and validates self-driving cars to ensure they meet the required quality and safety standards. This course can help build a foundation in the key principles of quality assurance, including testing methodologies, defect tracking, and quality control. Additionally, the course will cover topics such as self-driving car technology, industry standards, and safety-critical systems, which are essential for the quality assurance engineers working on self-driving cars.
Mechanical Engineer
A Mechanical Engineer designs, develops, and tests the mechanical systems of self-driving cars. This course can help build a foundation in the key principles of mechanical engineering, including solid mechanics, fluid mechanics, and thermodynamics. Additionally, the course will cover topics such as self-driving car architecture, sensor systems, and actuator systems, which are essential for the mechanical engineers working on self-driving cars.
Electrical Engineer
An Electrical Engineer designs, develops, and tests the electrical systems of self-driving cars. This course can help build a foundation in the key principles of electrical engineering, including circuit design, power electronics, and control systems. Additionally, the course will cover topics such as self-driving car architecture, sensor systems, and actuator systems, which are essential for the electrical engineers working on self-driving cars.
Systems Engineer
A Systems Engineer integrates the various components of self-driving cars into a single, functioning system. This course can help build a foundation in the key principles of systems engineering, including systems analysis, systems design, and systems integration. Additionally, the course will cover topics such as self-driving car architecture, sensor systems, and actuator systems, which are essential for the systems engineers working on self-driving cars.
Hardware Engineer
A Hardware Engineer designs, develops, and tests the hardware systems of self-driving cars. This course can help build a foundation in the key principles of hardware engineering, including electrical engineering, mechanical engineering, and embedded systems. Additionally, the course will cover topics such as self-driving car architecture, sensor systems, and actuator systems, which are essential for the hardware engineers working on self-driving cars.
Data Analyst
A Data Analyst collects, analyzes, and interprets data to help improve the performance of self-driving cars. This course can help build a foundation in the key principles of data analysis, including statistics, data mining, and machine learning. Additionally, the course will cover topics such as data collection, data cleaning, and data visualization, which are essential for the data analysts working on self-driving cars.

Reading list

We've selected eight books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Start on the road to a Self-Driving Car career.
Provides a comprehensive overview of robotics, vision, and control algorithms. It valuable resource for anyone interested in learning more about these topics.
Provides a comprehensive overview of probabilistic robotics. It valuable resource for anyone interested in learning more about this topic.
Provides a comprehensive overview of planning algorithms. It valuable resource for anyone interested in learning more about this topic.
Provides a comprehensive overview of control of mobile robots. It valuable resource for anyone interested in learning more about this topic.
Provides a comprehensive overview of pattern recognition and machine learning. It valuable resource for anyone interested in learning more about this topic.
Provides a comprehensive overview of autonomous mobile robots. It valuable resource for anyone interested in learning more about this topic.
Provides a comprehensive overview of autonomous driving. It valuable resource for anyone interested in learning more about this topic.

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