9 Best Data Structures and Algorithms Course Reviews in 2023 | Our Top Picks Covered In Detail

3 Top Data Structures and Algorithms Courses

Before taking this course, I had prior knowledge of the programming language in C and C++, as it's a mandatory requirement.

 I got over 23 lectures and 58 hours of content from this course.

This course covers the following topics:

• Introduction to common data Structures and Algorithms
• Matrices
• Arrays ADT
• Recursions
• Required set up for programming in C C++
• Review for Data Structures and Algorithms
• Strings
• Sparse matrix and polynomial representation

Who should take this course? This course is best suited for people with:

• A basic understanding of programming in C and C++
• People are looking to learn more about data structures and algorithms
• Anyone who wants to brush up on their knowledge of data structures and algorithms

Mode of study

• The course is available online, and one can access it anytime.
• One will need a computer with an internet connection to access the system.

By the end of this course, I was able to:

• Understand what data structures and basic algorithmic techniques are and how they are essential.
• Know how to use different data structures to store data efficiently
• Learn how to use different algorithms to manipulate data
• Understand the time and space complexity of various algorithms
• Be able to choose the correct algorithm for the job
• Have a good understanding of programming languages in C and C++.

How are the lectures handled?

• The lectures are delivered in a video format and are available online.
• The lecturer handles all the content on a whiteboard, explaining the details thoroughly.

I have found prior knowledge in programming helpful since it has made me understand complex concepts better.

How to enroll in data Structures and Algorithms Specialization?

After a basic understanding of computer programming, you can enroll by visiting the website and following the instructions, including making the subscriptions for the courses you wish to handle.

Courses offered in specialization include:

•  Algorithmic Toolbox 

•  Data science structures

•  Advanced Algorithms and Complexity  

•  Genome Assembly as a String Problem 

How does learning take place?

This course has several programming assignments which I found helpful because it makes you understand the concepts better .

The assignments gave me practice by enabling me to implement the algorithms and data structures covered in the lectures.

In addition, the assignments have helped me better understand how to use these algorithms and data structures to solve real-world problems. Note, I was required to complete several projects to finish the specialization.

What are the requirements?

This course requires basic knowledge of computer programming. If you are unfamiliar with basic programming, I recommend taking one of our introductory courses first.

Is any financial aid available?

No specific financial aid is available for this specialization, but I was lucky to be eligible for financial assistance from my university.

If finances are an issue, you can also check with your employer to see if they will cover the cost of the specialization. Lastly, you can also look into private scholarships or grants available to help you pay for the courses.

At the end of this course, I was able to:

• Understand the basics of data structures and algorithms

• Learn how to use data structures and algorithms to solve real-world problems

• Get the trade-offs between different data structures and algorithms

• Master the principles of asymptotic analysis.

The course has two parts:

• Basic Data structures: This is where you will learn about the different data structures in coding interviews, such as arrays, linked lists, trees, and hash tables. You will also learn about the various algorithms that one can use to solve problems with

• Algorithms are the second part; you will learn how to use these data structures and algorithms to solve coding interview questions.

How do you enroll in this course?

To enroll in the course, I visited Stephen Grider and Colt Steele's Websites, and I could purchase the system and access all lectures, quizzes, and assignments.

How long does it take to complete the course?

The course is self-paced, so I did it at my own pace. However, most students spend about 20-30 hours per week on the system.

What are the requirements for the course?

The only requirement for the course is a basic understanding of programming. If you do not know how to code, I recommend taking a beginner programming course before enrolling in this one.

What was I able to learn in this course? 

 At the end of this course, I was able to:

• Understand the different data structures and how to implement them in Python

• Traverse through data structures using various algorithms

• Solve coding interview questions using data structures and algorithms

Who should take this course?

I feel this course is for anyone who wants to prepare for their upcoming coding interview or improve their problem-solving skills.

How are lectures conducted?

The lectures for this course are through video. There are 84 lectures, each around 1-2 hours long. I love the fact that I can watch the lessons at my own pace and review them as often as needed. In addition, there are quizzes after every few lectures to ensure that I understand the resources.

Other things included in the course?

In addition to the lectures and quizzes, the course also includes assignments. After each section, I had a task to complete. These assignments were of help to me because of the much practice I did. 

Through this, I was able to prepare for my upcoming coding interview.

Additionally, the course also comes with a course forum. Here, I was able to ask questions, get help from other students, and discuss the material. Five articles are also part of the course to help you prepare for your coding interview.

To be excellent, you cannot avoid hard work and going an extra mile. The course is one of the most essential and marketable out there, so I would advise anyone willing to take the path to brace himself with resilience.

• Data visualization: This skill allows me to take complex data sets and turn them into easy-to-understand visuals. It helps present my findings to others and understand the data myself.

•  Data manipulation: This skill allows me to manipulate data sets to clean them or to perform analysis. It is a critical skill for performing accurate analysis.- 

• Statistical analysis: I get to use statistical methods to analyze data. It helps understand relationships between variables, as well as for making predictions.

Who should take this course?

This course is for anyone who wants to analyze data effectively, including students, professionals, and business owners.

No matter your experience level, this course can help you develop the skills you need to make better data-based decisions.

Why should I take this course?

I found that taking this course helped me develop essential data analysis skills.

One can apply these skills in various settings, which will help one make better decisions based on data. 

How long will this course take?

I took about four weeks to complete this course covering a different topic each week.

I was also able to go through the following modules:

1. Fundamentals of Data-Driven Decision-Making;

2. Research Questions for Data Analysis;

3. Organizing Data in Microsoft Excel;

4.  Statistical Analysis Using Microsoft Excel;

5. Interpretation of Outcomes;

6. Data Presentation and Visualization;

7. Introduction to Databases and SQL;

8. Looking Towards the Future.

After taking this course, I was able to:

• Understand the role of data and analytics in business decision-making;

• Develop skills in data manipulation and preparation;

• Apply a variety of data analysis techniques;

•  Understand the principles of statistical inference;

• Build predictive models and understand their limitations;

• Draw causal conclusions from data;

• Design experiments to test hypotheses;

• Analyze and interpret text data;

• Understand the business applications of data analysis methods.

I have found data analysis skills essential and applicable in most faces of life. The course, therefore, stands to be very crucial to as many as those who have an interest.

How do I enroll in this course?

I was able to visit the official website of the system. That's it! Just one click away.

This course was ideal for me because :

• I wanted to learn how to implement Python's critical data structures and algorithms.
• I felt it was preparing me for technical interviews
• I had some interest in advanced data structures such as Heap and Suffix Trees
• I wanted to know about dynamic programming, recursion, and graph algorithms

I learned how to:

• Implement critical data structures such as stacks, queues, trees, and hash tables.
• Use recursion to solve problems elegantly.
• Use dynamic programming to optimize your code.
• Find the shortest path in a graph using breadth-first search and Dijkstra's algorithms.
• Use suffix trees to solve problems involving text processing, how to implement Heap, a powerful Python library for efficient data structures much more!

How long does this course take?

The course is divided into four sections, each of which can be completed in one to two weeks. The total estimated time commitment for the system is 10-12 weeks.

Who should do this course?

This course is for students with prior experience programming in Python who want to learn about data structures and algorithms.

The level of knowledge of manipulating data in this course is fantastic. I have been fully equipped and can sort and interpret data of all kinds.

How do you enroll in this course?

This course is open to all students with a basic understanding of C++. If you are unfamiliar with the STL, I recommend taking our course Introduction to the Standard Template Library before enrolling in this course.

Enrolling in the C++ Data Structures in the STL course is easy. Register for the course by clicking on the "Enroll Now" button. Once registered, you can access the course materials and start learning immediately.

What I learned in this course

• In this course, I learned about the different data structures that are available in the STL;

• I also learned how to use these data structures to create efficient C++ programs;

• In addition, I got to know the different algorithms that are used to operate on data structures;

• Finally, I learned how to use the STL to develop efficient C++ programs.

How long does this course take?

What I love about this course is that it is self-paced and I get to complete it at my own pace. The course materials are available online, and you can access them anytime, anywhere.

What are the requirements for this course?

To take this course, you must have a basic understanding of C++. If you are unfamiliar with the STL, I recommend that you accept our course on Introduction to the Standard Template Library before enrolling in this course.

The fact that it is an online course has allowed me to study as I do other things simultaneously at my own pace.

What do you learn at the end of the course?

• You will learn everything you need to know to ace your following coding interview, including data structures, algorithms, and programming techniques.
• In addition, you will gain insights from industry experts on what it takes to be a successful programmer. By the end of the course, you will have the skills and knowledge necessary to impress your future employer and land the job of your dreams.

Course Content

The overview course has four sections:

1. Introduction to Coding Interviews

I could cover what to expect in a coding interview in this section. This section includes lectures on how to approach coding questions, what kind of questions to expect, and how to impress your interviewer.

In addition, interviews with industry experts provide insights into what it takes to be a successful programmer.

2. Data Structures

In this section, I learned the basics of data structures and how to use them effectively. This section includes lectures on arrays, linked lists, stacks, and queues. In addition, interviews with industry experts provide insights into what it takes to be a successful programmer.

3. Algorithms

The third section, Algorithms, covers the basics of algorithms and how to use them effectively. This section includes lectures on sorting, searching, and recursion. In addition, interviews with industry experts provide insights into what it takes to be a successful programmer.

4. Programming Techniques

The fourth section, Programming Techniques, covers the basics of programming techniques and how to use them effectively. 

This section includes lectures on topics such as object-oriented programming and design patterns. In addition, interviews with industry experts provide insights into what it takes to be a successful programmer.

I did a quiz testing my knowledge of the material at the end of each section. In addition, a final exam is at the end of the course.

Who this course is for:

This course is for Anyone who wants to learn everything they need to know to ace their following coding interview.

The system is also for Anyone who wants to gain insights from industry experts on what it takes to be a successful programmer.

Instructor:

Dr. William Fiset is a Software Engineer and instructor with over 15 years of industry experience. He has worked in various companies, from small startups to large tech firms like Google and Microsoft. He has a Ph.D. in Computer Science from the University of Waterloo and a master's in Software Engineering from the University of Toronto.

How is content delivered?

The course is through a combination of lectures, interviews, and quizzes. The classes are video-based, and the examinations are in multiple-choice format, making me comfortable.

Duration of course:

The course is self-paced, and you can complete it at your own pace. It will take approximately 10 hours to complete the course.

Course requirements

No prior knowledge or experience is required to take this course. However, a basic understanding of computer programming would be beneficial.

Course Objectives

By the end of this course, participants will be able to:

• Understand the basics of data analysis

• Apply data analysis techniques to real-world problems

• Make more effective decisions using data.

Course Outline

Module 1: Introduction to Data Analysis

Here you will be able to learn

• What is data analysis?

• Why is data analysis critical?

• Types of data

• Data collection methods

Module 2: Data Cleaning and Exploration

In this module, you will be able to understand the following:

• Importance of clean data

• Data cleaning techniques

• Exploratory data analysis

Module 3: Data Visualization

In this module, you will learn

• Introduction to data visualization

• Types of visualizations

• Best practices for data visualization

Module 4: Data Analysis in Practice

This module covers

• Applying data analysis to real-world problems

• Case studies and examples

• Course Format: This course will be delivered as a series of lectures, discussions, and hands-on exercises.

Course Materials

All participants will receive a course manual and other supporting materials.

Cancellation Policy

I loved the fact that if you need to cancel your registration, you can do so at least two weeks before the course date. You will receive a full refund if cancellation is made more than two weeks before the course date.

That's why they're perfect for systems with a high volume of requests - like those found on social media websites.

Types of structures found in Java Course:

1. Stacks and Queues

A stack is a data structure that allows me to store and access data in a Last In First Out (LIFO) manner.

It means that the last element I add to the stack will be the first one I can remove.

Queues are also an important data structure. The queue allows me to insert new elements at any position.

The main difference between queues and stacks is how they handle collisions. When more elements are on top of each other than space, the items collide on top of each other. This is called stack overflow or queue underflow, depending on which type of data structure occurs.

2. Linked Lists

A linked list is a data structure that stores a sequence of elements. Each element is called a node, and each node has a reference to the next node in the series.

Linked lists are often used to implement queues and stacks, and Queues provide a first-in-first-out (FIFO) abstraction, while stacks provide last-in-last-out (LIFO).

3. Tree Traversals

Three main types of tree traversals are Inorder, Preorder, and Postorder.

• In order, traversal visits the left child, the root, and finally, the right child.
• Preorder traversal visits the core first, then the left child, and eventually the right child.
• Postorder traversal visits the left child first, then the right child, and finally the root.

4. Graphs

There are two of the most popular methods for representing graphs:

• Adjacency Lists: These are an array of arrays where each inner display is an edge's source node and the target node.
• Adjacency Matrices are 2D arrays that store nodes as rows and edges as columns, with entries being either 0 or 1 depending on whether there is an edge between two nodes.

5. Sorting Algorithms

Sorting algorithms are a fundamental part of any programmer's toolkit. You can use them to optimize code, improve performance, and make your life as a programmer easier.

6. Hashing Algorithms.

A hash table is a data structure that allows me to store data in an array-like form but can access it using a key instead of an index.

Hash tables are used for quick lookup and insertion of data and are often used in conjunction with other data structures, such as linked lists.

There are many different hashing algorithms, but the division method is the most common.

In this course, we'll learn about

• Operations concerning advanced data structures that go beyond the basics.
• How to implement these data structures in code and use them to solve real-world problems.
• How to confidently use advanced data structures in your programs.
• The primary data structures and when you should use them.

There is nothing that comes easily. This course taught me that complexity is not a synonym for impossibility. It indeed took me a lot of hard work to complete the course.