Coding Interview Preparation (Coursera)

Offered by Meta,
Coding Interview Preparation (Coursera)

The final course in this program will help prepare you for the unique aspects of a coding job interview, with approaches to problem-solving and computer science foundations needed to land the job. Ultimately you’ll gain strategic insights and tips for successful interviewing.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

By the end of this course, you'll have knowledge of:
• Appropriate communication during a coding interview
•  Successful interviewing strategies
• Using pseudocode
•  The fundamentals of computer science
• The capabilities of data structures and how to implement them
• How to review data structures in the context of coding interviews
•  The concept of algorithms and common approaches to working with them
•  How to visualize an algorithm
• Combining new and previously learned coding patterns to solve problems
Ideally, you should have completed all the courses in this professional certificate.

This course can be applied to multiple Specializations or Professional Certificates programs. Completing this course will count towards your learning in any of the following programs:
Meta Front-End Developer Professional Certificate
Meta Back-End Developer Professional Certificate

What You Will Learn

  • Prepare for a coding interview
  • Prepare for a Meta interview
  • Solve problems using code

Syllabus

WEEK 1
Introduction to the coding interview
In this introductory module, you'll learn about a coding interview, what it could consist of, and the types of coding interviews you might encounter. You’ll learn about how to prepare for a coding interview, focusing on communication and working with pseudocode. You will also get an introduction to computer science, including the fundamental concepts of Binary, Big O notation, and time and space complexity.

WEEK 2
Introduction to Data Structures
The second module of this course covers data structures. You'll learn about the implementation and capabilities of data structures between various programming languages and the similar patterns of the overarching architecture. You will learn about basic data structures, such as strings, integers, arrays and objects, before moving on to collection data structures, including lists, stacks and trees, and advanced data structures, such as hash tables, heaps and graphs.

WEEK 3
Introduction to Algorithms
In this module, you'll learn about algorithms. You'll cover common approaches to sorting and searching with algorithms. You’ll also explore the time and space complexity aspects of both sorting and searching. You will then learn more about working with algorithms, demonstrating how to visualize and problem solve with algorithmic approaches, such as divide and conquer, greedy algorithms and dynamic programming.

WEEK 4
Final project
In this module, you will be assessed on the key concepts and topics covered in the course.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Advanced Data Structures in Java (Coursera) Coursera
University of California, San Diego

Advanced Data Structures in Java (Coursera)

How does Google Maps plan the best route for getting around town given current traffic conditions? How does an internet router forward packets of network traffic to minimize delay? How does an aid group allocate resources to its affiliated local partners? To solve such problems, we first represent the key pieces of data in a complex data structure. In this course, you’ll learn about data structures, like graphs, that are fundamental for working with structured real world data.

Jun 22nd 2026
5-12 Weeks
Approximation Algorithms (Coursera) Coursera
EIT Digital

Approximation Algorithms (Coursera)

Many real-world algorithmic problems cannot be solved efficiently using traditional algorithmic tools, for example because the problems are NP-hard. The goal of this course is to become familiar with important algorithmic concepts and techniques needed to effectively deal with such problems. These techniques apply when we don't require the optimal solution to certain problems, but an approximation that is close to the optimal solution. We will see how to efficiently find such approximations.

Jun 26th 2026
4 Weeks
Unordered Data Structures (Coursera) Coursera
University of Illinois at Urbana-Champaign

Unordered Data Structures (Coursera)

The Unordered Data Structures course covers the data structures and algorithms needed to implement hash tables, disjoint sets and graphs. These fundamental data structures are useful for unordered data. For example, a hash table provides immediate access to data indexed by an arbitrary key value, that could be a number (such as a memory address for cached memory), a URL (such as for a web cache) or a dictionary.

Jun 24th 2026
4 Weeks
Parallel programming (Coursera) Coursera
École Polytechnique Fédérale de Lausanne

Parallel programming (Coursera)

With every smartphone and computer now boasting multiple processors, the use of functional ideas to facilitate parallel programming is becoming increasingly widespread. In this course, you'll learn the fundamentals of parallel programming, from task parallelism to data parallelism. In particular, you'll see how many familiar ideas from functional programming map perfectly to to the data parallel paradigm.

Jun 22nd 2026
4 Weeks
Packet Switching Networks and Algorithms (Coursera) Coursera
University of Colorado System

Packet Switching Networks and Algorithms (Coursera)

In this course, we deal with the general issues regarding packet switching networks. We discuss packet networks from two perspectives. One perspective involves external view of the network, and is concerned with services that the network provides to the transport layer that operates above it at the end systems. The second perspective is concerned with the internal operation of a network, including approaches directing information across the network, addressing and routing procedures, as well as congestion control inside the network.

Jun 22nd 2026
5-12 Weeks
Data Structures (Coursera) Coursera
University of California, San Diego,Higher School of Economics - HSE University

Data Structures (Coursera)

A good algorithm usually comes together with a set of good data structures that allow the algorithm to manipulate the data efficiently. In this course, we consider the common data structures that are used in various computational problems. You will learn how these data structures are implemented in different programming languages and will practice implementing them in our programming assignments.

Jun 22nd 2026
5-12 Weeks
Crash Course on Python (Coursera) Coursera
Google

Crash Course on Python (Coursera)

This course is designed to teach you the foundations in order to write simple programs in Python using the most common structures. No previous exposure to programming is needed. By the end of this course, you'll understand the benefits of programming in IT roles; be able to write simple programs using Python; figure out how the building blocks of programming fit together; and combine all of this knowledge to solve a complex programming problem.

Jun 23rd 2026
5-12 Weeks
Advanced Algorithms and Complexity (Coursera) Coursera
University of California, San Diego,Higher School of Economics - HSE University

Advanced Algorithms and Complexity (Coursera)

You've learned the basic algorithms now and are ready to step into the area of more complex problems and algorithms to solve them. Advanced algorithms build upon basic ones and use new ideas. We will start with networks flows which are used in more typical applications such as optimal matchings, finding disjoint paths and flight scheduling as well as more surprising ones like image segmentation in computer vision.

Jun 22nd 2026
5-12 Weeks
Number Theory and Cryptography (Coursera) Coursera
University of California, San Diego,Higher School of Economics - HSE University

Number Theory and Cryptography (Coursera)

We all learn numbers from the childhood. Some of us like to count, others hate it, but any person uses numbers everyday to buy things, pay for services, estimated time and necessary resources. People have been wondering about numbers’ properties for thousands of years. And for thousands of years it was more or less just a game that was only interesting for pure mathematicians. Famous 20th century mathematician G.H. Hardy once said “The Theory of Numbers has always been regarded as one of the most obviously useless branches of Pure Mathematics”. Just 30 years after his death, an algorithm for encryption of secret messages was developed using achievements of number theory. It was called RSA after the names of its authors, and its implementation is probably the most frequently used computer program in the word nowadays.

Jun 22nd 2026
4 Weeks
Algorithmic Toolbox (Coursera) Coursera
University of California, San Diego,Higher School of Economics - HSE University

Algorithmic Toolbox (Coursera)

The course covers basic algorithmic techniques and ideas for computational problems arising frequently in practical applications: sorting and searching, divide and conquer, greedy algorithms, dynamic programming. We will learn a lot of theory: how to sort data and how it helps for searching; how to break a large problem into pieces and solve them recursively; when it makes sense to proceed greedily; how dynamic programming is used in genomic studies. You will practice solving computational problems, designing new algorithms, and implementing solutions efficiently (so that they run in less than a second).

Jun 22nd 2026
5-12 Weeks
Practical Machine Learning (Coursera) Coursera
Johns Hopkins University

Practical Machine Learning (Coursera)

One of the most common tasks performed by data scientists and data analysts are prediction and machine learning. This course will cover the basic components of building and applying prediction functions with an emphasis on practical applications. The course will provide basic grounding in concepts such as training and tests sets, overfitting, and error rates.

Jun 22nd 2026
4 Weeks