Algorithms for Searching, Sorting, and Indexing from Coursera

This course covers basics of algorithm design and analysis, as well as algorithms for sorting arrays, data structures such as priority queues, hash functions, and applications such as Bloom filters.

Algorithms for Searching, Sorting, and Indexing can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.

What's inside

Syllabus

Basics of Algorithms Through Searching and Sorting

In this module the student will learn the very basics of algorithms through three examples: insertion sort (sort an array in ascending/descending order); binary search: search whether an element is present in a sorted array and if yes, find its index; and merge sort (a faster method for sorting an array). Through these algorithms the student will be introduced to the analysis of algorithms -- i.e, proving that the algorithm is correct for the task it has been designed for and establishing a bound on how the time taken to execute the algorithm grows as a function of input. The student is also exposed to the notion of a faster algorithm and asymptotic complexity through the O, big-Omega and big-Theta notations.

Heaps and Hashtable Data Structures

In this module, the student will learn about the basics of data structures that organize data to make certain types of operations faster. The module starts with a broad introduction to data structures and talks about some simple data structures such as first-in first out queues and last-in first out stack. Next, we introduce the heap data structure and the basic properties of heaps. This is followed by algorithms for insertion, deletion and finding the minimum element of a heap along with their time complexities. Finally, we will study the priority queue data structure and showcase some applications.

Randomization: Quicksort, Quickselect, and Hashtables

We will go through the quicksort and quickselect algorithms for sorting and selecting the kth smallest element in an array efficiently. This will also be an introduction to the role of randomization in algorithm design. Next, we will study hashtables: a highly useful data structure that allows for efficient search and retrieval from large amounts of data. We will learn about the basic principles of hash-table and operations on hashtables.

Applications of Hashtables

In this module, we will learn randomized pivot selection for quicksort and quickselect. We will learn how to analyze the complexity of the randomized quicksort/quickselect algorithms. We will learn open address hashing: a technique that simplifies hashtable design. Next we will study the design of hash functions and their analysis. Finally, we present and analyze Bloom filters that are used in various applications such as querying streaming data and counting.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Provides a foundation in algorithms and data structures for learners interested in computer science or data science

Taught by an experienced instructor from the University of Colorado Boulder, a leading institution in computer science

Examines core concepts and algorithms used in various applications, making it relevant for both industry and academia

Introduces fundamental algorithm design techniques, including sorting, searching, and indexing

Presents data structures such as heaps and hashtables, which are widely used in software development

Lays the groundwork for further study in algorithm design and optimization

Reviews summary

Algorithms for searching, sorting, engaging learning

Learners say this course is largely positive and covers searching, sorting, and indexing well. Instruction is clear and concise, featuring engaging lectures, informative videos, and insightful materials. The assignments are challenging and practical, providing ample opportunity to apply learned concepts. The use of python and jupyter notebooks is particularly beneficial for learners with programming experience.

Course leverages python and jupyter notebooks.

"The python notebooks are awesome"

"I really liked this course, it provides lots of new insights and very good explanations into searching big data using techniques I did not know before. Exercises are nicely done using Jupyter."

"Excellent Course! Clear explanations by the professor and clear instructions in the Jupyter notebook for the programming assignments."

Exercises and programming assignments reinforce learning.

"assigns not overly challenging but rather enlightening"

"The programming exercises are well designed to help deepening the understanding of the subject."

"The assignments are challenging but not overwhelming"

Explanations are thorough and well-paced.

"clear expositions of the material"

"The instuctor is amazing. I like it how he explains difficult concepts in a clear manner."

"This course was one of the best online courses I have taken so far."

Labs can be difficult to run and submit.

"too many technical issues running and submitting the labs"

"The time estimate for this course is inaccurate."

"The lectures are super great! The professor explains everything clearly.However, the assignments are not that polished. There are tons of typos."

Some mathematical proofs can be challenging.

"The algorithmic analysis always left me bewildered by the mathimatical proofs being used."

"some rigorous mathematic proofs are presented in this course"

"Week 1 about Hashtable is a little difficult to understand!"

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 Algorithms for Searching, Sorting, and Indexing with these activities:

Review Basic Python Programming

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Ensuring a strong foundation in Python programming will facilitate your understanding of the course material.

Browse courses on Python

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Review basic Python syntax, data types, and control flow.
Complete online tutorials or exercises to reinforce your understanding.

Gather Resources on Algorithm Design

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Consolidating relevant resources in one place enables you to easily access them throughout the course, enhancing your learning experience.

Browse courses on Algorithm Design

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Search for books, articles, videos, and online courses related to algorithm design.
Organize the resources into a central location, such as a digital folder or a shared online space.

Review 'Introduction to Algorithms' by Cormen, Leiserson, Rivest, and Stein

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Reinforce understanding of fundamental concepts covered in the course, deepening your understanding of time and space complexity analysis.

View Introduction to Algorithms, fourth edition on Amazon

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Read each chapter thoroughly, taking notes on key concepts and algorithms.
Solve practice problems at the end of each chapter to test your understanding.
Participate in online discussion forums to clarify any doubts and engage with other learners.

Five other activities

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Follow tutorials on Heaps and Hashtables

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Supplement your understanding of these essential data structures by exploring online tutorials that provide step-by-step explanations and examples.

Browse courses on Heaps

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Identify reputable online platforms or instructors offering tutorials on heaps and hashtables.
Select tutorials that align with your learning style and pace.
Follow the tutorials meticulously, taking notes on key implementation details.

Form a Study Group for Algorithm Analysis

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Collaborative learning through peer study groups enhances understanding by allowing you to exchange ideas, clarify concepts, and work through problems together.

Browse courses on Algorithm Analysis

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Identify classmates who share similar learning goals and interests.
Establish regular meeting times and a designated study space.
Take turns presenting concepts, leading discussions, and solving problems.

Solve Coding Challenges on LeetCode

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Sharpen your algorithmic problem-solving skills by tackling coding challenges on LeetCode, a platform that hosts a vast collection of problems tailored for algorithm design and analysis.

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Create an account on LeetCode.
Select problems that align with the topics covered in the course.
Attempt to solve the problems on your own, referring to the discussion forums for hints and solutions if needed.

Implement a Heap Data Structure in Python

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Practical implementation of a heap data structure in Python will solidify your understanding of its operations and properties.

Browse courses on Heap

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Review the theory and implementation details of a heap data structure.
Choose a Python programming environment and familiarize yourself with its syntax.
Implement the heap data structure, including methods for insertion, deletion, and finding the minimum element.

Contribute to an Open Source Repository on Algorithm Implementations

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Practically applying your knowledge by contributing to an open source repository deepens your understanding and connects you with a community of developers.

Browse courses on Open Source

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Identify an open source repository on GitHub or other platforms that aligns with the course content.
Review the repository's documentation and coding guidelines.
Select an issue to work on and submit a pull request with your proposed solution.

Career center

Learners who complete Algorithms for Searching, Sorting, and Indexing will develop knowledge and skills that may be useful to these careers:

Algorithm Engineer

Algorithm Engineers research and design new algorithms to solve complex problems. Taking this Algorithms for Searching, Sorting, and Indexing course will be extremely helpful to you in this career as it covers basic algorithm design and analysis, which are the bread and butter of algorithm engineering.

See salaries and explore the career path for Algorithm Engineer

Data Architect

Data Architects design, build, and maintain data storage and management systems. Taking this Algorithms for Searching, Sorting, and Indexing course will prove invaluable to you in this role, as it will strengthen your foundational knowledge of algorithms, data structures, and databases.

See salaries and explore the career path for Data Architect

Quant Analyst

Quant Analysts analyze and interpret quantitative data to make recommendations for investment or finance decisions. Taking this Algorithms for Searching, Sorting, and Indexing course will prove quite valuable to you in developing the programming and analytical skills used by Quants to make predictions and inform financial decisions.

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IT Consultant

IT Consultants help organizations improve their IT systems and processes. Taking this Algorithms for Searching, Sorting, and Indexing course will be very useful for IT Consulting as it will strengthen your foundational knowledge of algorithms, data structures, and databases, which are all very important for optimizing IT systems.

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Computer Scientist

Computer Scientists analyze problems and design computer-based solutions. Taking this Algorithms for Searching, Sorting, and Indexing course provides a strong foundation in fundamental programming concepts, which is necessary to working in this occupation. Additionally, the data structures and algorithms knowledge taught in this course will give you a leg-up on computer science fundamentals and common algorithms interviewers will expect you to be familiar with.

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Software Developer

Software Developers work with end user businesses to create or improve software. Taking this Algorithms for Searching, Sorting, and Indexing course will give you a strong mathematical foundation for developing software, as well as experience with designing and analyzing algorithms, which will help prepare you for common coding questions.

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Data Scientist

Data Scientists collaborate with domain experts to collect and analyze data, then provide insights and actionable recommendations. Taking this Algorithms for Searching, Sorting, and Indexing course will be useful as you learn methods for processing and analyzing data, which are essential for effective data science work.

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Data Engineer

Data Engineers maintain and transform data to support business intelligence and analytics. Taking this Algorithms for Searching, Sorting, and Indexing course may be useful to you in this role as it presents fundamental concepts in algorithm design and analysis, which will give you a leg up on understanding data structure and algorithms in the context of data engineering.

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Software Architect

Software Architects are responsible for the overall design and architecture of software systems. Taking this Algorithms for Searching, Sorting, and Indexing course may be helpful to you in developing the skills needed to design and implement complex software systems, particularly in understanding how algorithms will scale in larger systems.

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Statistician

Statisticians collect, analyze, and interpret data. Taking this Algorithms for Searching, Sorting, and Indexing course may be useful to you as it gives an overview of algorithm design and analysis, which is valuable to your role, especially if it involves developing statistical models.

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Business Analyst

Business Analysts help organizations improve their performance. Taking this Algorithms for Searching, Sorting, and Indexing course may provide you some benefit as it will help you develop analytical skills to identify problems and recommend solutions.

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Financial Analyst

Financial Analysts analyze financial data to make investment recommendations. Taking this Algorithms for Searching, Sorting, and Indexing course will likely be helpful to you in developing your analytical skills for financial planning.

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Information Security Analyst

Information Security Analysts protect organizations and data from cyberattacks. Taking this Algorithms for Searching, Sorting, and Indexing course may be somewhat helpful as you will learn to analyze algorithms and data structures, which is useful if you want to pursue a career in cybersecurity.

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Product Manager

Product Managers work with engineers and designers to build and improve products. Taking this Algorithms for Searching, Sorting, and Indexing course will provide you with a background in the algorithms and data structures that power software products.

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UX Designer

UX Designers create user-friendly interfaces for websites and apps. This Algorithms for Searching, Sorting, and Indexing course will not provide you with much benefit.

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