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Andy Brown, Andrew Paster, Anthony Navarro, Tarin Ziyaee, Elecia White, Cezanne Camacho, and Sebastian Thrun
Algorithmic thinking is a skill you’ll refine throughout your career. In this course you’ll focus on frequently used data structures and algorithms.

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What's inside

Syllabus

A systematic way of approaching and breaking down problems.
The list isn't the only structure for storing data! In this lesson you'll learn about sets, dictionaries and other Python data structures.
Read more
When programming a car to drive itself you run into problems. Many of these are "search" problems. In this lesson you'll learn what search problems are and several algorithms for solving them.
In this lesson you will actually implement a Google-maps style routing algorithm using A star search.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Examines concepts and techniques for data structure choices and designing solutions to algorithmic problems using Python
Taught by instructors who have been recognized for their computer science work
Recommended for intermediate learners who have familiarity with programming concepts

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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 Navigating Data Structures with these activities:
Review Python data structures and algorithms
Refreshes foundational Python data structures and algorithms concepts to ensure success in this course.
Browse courses on Data Structures
Show steps
  • Review Python data structures such as lists, dictionaries, and sets
  • Review basic algorithms such as sorting and searching
  • Practice implementing these concepts in Python code
Participate in online forums or discussion groups
Facilitates peer learning and exposure to diverse perspectives on course topics.
Show steps
  • Join online forums or discussion groups related to the course
  • Read and respond to discussions
  • Ask questions and seek clarification from others
  • Share your own insights and experiences
Follow online tutorials on search algorithms
Provides additional practice and reinforcement of search algorithm concepts covered in the course.
Browse courses on Search Algorithms
Show steps
  • Find online tutorials on search algorithms such as breadth-first search, depth-first search, and A* search
  • Follow the tutorials and implement the algorithms in Python code
  • Test and debug your code to ensure it works correctly
Three other activities
Expand to see all activities and additional details
Show all six activities
Solve coding problems on LeetCode or HackerRank
Provides hands-on practice in applying algorithmic thinking to solve real-world problems.
Browse courses on Algorithms
Show steps
  • Sign up for LeetCode or HackerRank
  • Select coding problems that are relevant to the course topics
  • Solve the problems using Python code
  • Review your solutions and identify areas for improvement
Lead a study group or tutor other students
Strengthens understanding of the course material through teaching and reinforcing concepts to others.
Browse courses on Algorithmic Thinking
Show steps
  • Organize a study group with classmates
  • Prepare materials to review course concepts
  • Lead discussions and answer questions from other students
  • Provide feedback and support to help others succeed
Develop a Python program to solve a real-world problem
Demonstrates the ability to apply algorithmic thinking to practical problems and improve problem-solving skills.
Browse courses on Algorithmic Thinking
Show steps
  • Identify a real-world problem that can be solved using algorithmic techniques
  • Design and implement a Python program that solves the problem
  • Test and debug your program to ensure it works correctly
  • Document your program and explain the algorithms used

Career center

Learners who complete Navigating Data Structures will develop knowledge and skills that may be useful to these careers:
Data Structures Engineer
Data Structures Engineers excel at using programming knowledge to solve complex problems and to optimize the efficiency of data retrieval within various systems. The Navigating Data Structures course helps students master algorithms and fundamental data structures, which are all necessary skills for succeeding in this role. By understanding how to manage data efficiently, Data Structures Engineers can build high-impact products.
Software Engineer
Software Engineers with expertise in data structures manipulate data and solve advanced problems in real-world scenarios. Navigating Data Structures delves into algorithms and data structures, providing a strong foundation to support success in this field. With the knowledge gained from this course, Software Engineers are better able to build and maintain scalable, efficient software systems.
Data Analyst
Data Analysts are responsible for collecting and interpreting large amounts of data to drive decision-making. This course, Navigating Data Structures, allows them to develop the algorithmic thinking and data structure skills essential for organizing and analyzing data effectively. Through hands-on exercises, they learn to solve complex problems and make valuable contributions to data analysis initiatives.
Data Engineer
Navigating Data Structures provides Data Engineers with a comprehensive understanding of data organization and retrieval algorithms. The course covers advanced data structures and their implementation techniques, empowering them to build reliable, high-performance data pipelines and databases. By mastering these concepts, Data Engineers can effectively manage and process large volumes of data, enabling data-driven decision-making.
Cloud Engineer
Cloud Engineers leverage their understanding of data structures and algorithms to design, implement, and maintain cloud-based solutions. In Navigating Data Structures, they gain expertise in working with large datasets and developing efficient storage and retrieval systems. This course enhances their ability to build scalable, reliable, and cost-effective cloud architectures.
DevOps Engineer
DevOps Engineers benefit from Navigating Data Structures by gaining proficiency in handling complex data structures. This course strengthens their ability to automate build and deployment pipelines, enabling efficient software delivery. By mastering data structures, they optimize resource allocation and streamline collaboration between development and operations teams.
Data Scientist
Data Scientists leverage data structures to manage and analyze complex datasets. Navigating Data Structures equips them with a deep understanding of various data structures and their applications in real-world data science scenarios. Through hands-on exercises, they gain proficiency in selecting and implementing appropriate data structures, enabling them to extract valuable insights and drive data-informed decision-making.
Machine Learning Engineer
Machine Learning Engineers utilize data structures to store, process, and analyze vast amounts of data for machine learning models. Navigating Data Structures offers a solid foundation in data organization techniques and algorithms. The course's focus on practical examples and hands-on exercises equips Machine Learning Engineers with the skills to implement effective data structures for large-scale data processing and model development.
Algorithm Developer
Navigating Data Structures serves as a valuable resource for Algorithm Developers, who design and implement efficient algorithms. This course provides a thorough grounding in fundamental data structures that support algorithm design. By understanding the behavior and time complexity of different structures, Algorithm Developers can develop optimal solutions to real-world problems, enhancing software performance and efficiency.
Database Administrator
Database Administrators are responsible for managing and optimizing databases. Navigating Data Structures provides a solid foundation in data structures and algorithms, equipping them with the skills to design and implement efficient database systems. By understanding the underlying structures of databases, they can optimize data storage and retrieval, improve query performance, and ensure data integrity.
Software Architect
Navigating Data Structures empowers Software Architects with the knowledge to design and develop software systems with efficient data management. This course covers advanced data structures and algorithms, providing a deep understanding of how data is organized and accessed. By leveraging these principles, Software Architects can create scalable, reliable, and maintainable software applications.
Artificial Intelligence Engineer
Navigating Data Structures offers a valuable foundation for Artificial Intelligence Engineers who leverage data structures to develop intelligent systems. This course provides insights into the internal workings of data structures and their applications in AI algorithms. By mastering these concepts, Artificial Intelligence Engineers can optimize data processing, enhance model performance, and build robust AI systems.
Blockchain Developer
Navigating Data Structures is a valuable resource for Blockchain Developers who need to manage complex data within distributed ledger systems. This course provides a comprehensive understanding of data structures and algorithms, empowering them to optimize blockchain performance and security. By mastering data structures, Blockchain Developers can create efficient and secure blockchain applications that meet the demands of the digital economy.
Web Developer
Web Developers can enhance their skills by taking Navigating Data Structures to gain insights into organizing and managing data within web applications. This course covers fundamental data structures and algorithms, providing a foundation for optimizing website performance and user experience. By understanding data structures, Web Developers can create efficient and scalable web applications that meet the demands of modern web development.
Quantitative Analyst
Navigating Data Structures provides Quantitative Analysts with a strong foundation in data structures and algorithms, essential for handling complex financial data. This course covers advanced data structures and their applications in quantitative finance, enabling analysts to efficiently process and analyze large datasets. By understanding data structures, they can develop robust financial models, optimize trading strategies, and make data-driven decisions.

Reading list

We've selected 13 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 Navigating Data Structures.
This classic textbook provides a rigorous foundation in algorithm design and analysis. It covers a wide range of topics, complementing the course's focus on specific data structures and algorithms.
Provides a comprehensive overview of algorithms and data structures, covering fundamental concepts, analysis techniques, and real-world applications. It valuable reference for deeper understanding of the topics covered in the course.
Focuses on Python implementations of data structures and algorithms, providing practical insights into their design and application. It complements the course's theoretical concepts with real-world examples.
This popular book provides a comprehensive guide to preparing for coding interviews. It covers a wide range of topics, including data structures, algorithms, and problem-solving strategies.
This practical guide provides a collection of algorithm design techniques and examples. It valuable resource for learners looking to enhance their problem-solving skills and develop efficient algorithms.
Provides a theoretical foundation for computer science, covering topics such as automata theory, computability, and complexity theory. It complements the course's focus on practical algorithms with a deeper understanding of their underlying principles.
Presents data structures and algorithms in a visually engaging and interactive manner. It good resource for learners who prefer a more hands-on approach and want to grasp the concepts intuitively.
Provides a comprehensive introduction to Python programming. It valuable resource for learners who want to develop a strong foundation in the language used in the course.
Presents a collection of programming challenges and solutions. It great resource for learners who want to practice their problem-solving skills and prepare for coding competitions.
Focuses on algorithms and data structures designed for handling massive datasets. It provides insights into the challenges and techniques involved in working with Big Data.
Provides a comprehensive introduction to reinforcement learning, a machine learning technique used in many applications involving decision-making and optimization. It complements the course's focus on algorithms with insights into a different approach to problem-solving.

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