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Best courses to learn Data Structures & Algorithms
Data Structures and Algorithms
Welcome to the Data Structures and Algorithms course! Dive into the essential principles and techniques that form the backbone of computer science and software development. This comprehensive course explores the efficient organization, storage, and manipulation of data using various data structures such as arrays, linked lists, stacks, queues, hash tables, trees, and graphs. You will learn how to implement these structures in your code, optimize their performance, and solve complex computational problems through algorithm design and analysis. Master key concepts including sorting algorithms l
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Ordered Data Structures
In this course, you will learn new data structures for efficiently storing and retrieving data that is structured in an ordered sequence. Such data includes an alphabetical list of names, a family tree, a calendar of events or an inventory organized by part numbers. The specific data structures covered by this course include arrays, linked lists, queues, stacks, trees, binary trees, AVL trees, B-trees and heaps. This course also shows, through algorithm complexity analysis, how these structures enable the fastest algorithms to search and sort data.
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Foundations of AI in Game Development
This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. In this course, you will dive deep into the foundational concepts of Artificial Intelligence (AI) and its application in game development. By exploring AI techniques in Unity, you’ll learn how to implement AI-driven characters, create realistic movement, and develop advanced pathfinding systems. As you progress, you will discover how mathematics, physics, and algorithms
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Fundamentals of Unity Android Game Development
This course is your gateway to mastering Android game development with Unity 2022. You'll start by learning how to set up Unity and develop a basic understanding of the platform. From there, you will dive into building a simple yet engaging 3D endless runner game, learning how to create game levels, control player movement, and handle game mechanics such as platform spawning and object destruction. Next, the course takes you on an exciting journey to develop a 3D zigzag game, guiding you through advanced mechanics like player control via touch input, spawning platforms with random algorithms,
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Foundations of Artificial Intelligence
This course introduces learners to the core principles of artificial intelligence, including its history, definitions, and the role of data in AI. You’ll explore algorithms, specialized hardware, and delve into machine learning and deep learning fundamentals. Ethical considerations around AI, especially generative AI (GenAI), will also be discussed, ensuring you understand the broader impact AI has on society and the workforce. With clear explanations and real-world examples, the course ensures you not only learn theoretical concepts but also understand their practical implications. You’
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Introduction to Embedded Machine Learning
Machine learning (ML) allows us to teach computers to make predictions and decisions based on data and learn from experiences. In recent years, incredible optimizations have been made to machine learning algorithms, software frameworks, and embedded hardware. Thanks to this, running deep neural networks and other complex machine learning algorithms is possible on low-power devices like microcontrollers. This course will give you a broad overview of how machine learning works, how to train neural networks, and how to deploy those networks to microcontrollers, which is known as embedded machine
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AI and Content Recommendation
Build your subject-matter expertise This course is part of the AI in Media specialisation. When you enrol in this course; you'll also be enrolled in this Specialisation. ● Learn new concepts from industry experts ● Gain a foundational understanding of modern strategic tools ● Develop job-relevant skills with hands-on scenario-based projects ● Earn a shareable career certificate About this Course In a world where content is tailored to users, understanding recommendation algorithms is vital for any media professional. This course explores how organisations use machine learning to build 'mode
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Deep Reinforcement Learning: From Theory to Practice
How can reinforcement learning scale beyond small tabular problems to high-dimensional environments such as games, robotics, and autonomous decision-making? This course introduces deep reinforcement learning, where reinforcement-learning algorithms are combined with neural-network-based function approximation. Learners begin by studying why tabular methods break down in large or continuous state spaces and how value functions, action-value functions, and policies can be represented by parameterized models. The course then develops value-based deep reinforcement learning methods, including fit
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Introduction to Computer Vision
In the first course of the Computer Vision for Engineering and Science specialization, you’ll be introduced to computer vision. You'll learn and use the most common algorithms for feature detection, extraction, and matching to align satellite images and stitch images together to create a single image of a larger scene. Features are used in applications like motion estimation, object tracking, and machine learning. You’ll use features to estimate geometric transformations between images and perform image registration. Registration is important whenever you need to compare images of the same s
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Exploring Algorithmic Bias as a Policy Issue: A Teach-Out
This Teach Out does not issue certificates of completion. Algorithms – and algorithmic bias – are making regular appearances in the news, and increasingly, are being recognized as a policy issue. But what is an algorithm, exactly? And what does it mean when someone describes an algorithm as biased? This Teach-Out will encourage policy makers, agency leaders, and others in similar positions to identify algorithms that are already in use and make connections to broader ideas about fairness, justice, and equity. After completing the Teach-Out, learners will be able to participate in discussions
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Deep Learning with PyTorch
This course offers a comprehensive and practical introduction to deep learning using PyTorch, a leading open-source framework. Learners will develop a solid understanding of foundational concepts such as neural networks, activation functions, forward and backward propagation, and optimization algorithms. Through a structured progression, the course covers essential architectures including perceptrons, multi-layer networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), long short-term memory (LSTM) models, and Transformers. Learners will apply these models to real-wor
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Analyze Video Data Using OpenCV and Python
By the end of this course, learners will be able to analyze video data, apply color models, implement image preprocessing techniques, and build object detection and tracking solutions using OpenCV and Python. They will gain the ability to process real-time and recorded video streams, extract meaningful visual features, and apply motion analysis algorithms to solve practical computer vision problems. This course benefits learners by providing a structured, hands-on pathway from foundational concepts to advanced video analytics techniques. Learners will develop industry-relevant skills in image
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Introduction to Computer Vision
Introduction to Computer Vision guides learners through the essential algorithms and methods to help computers 'see' and interpret visual data. You will first learn the core concepts and techniques that have been traditionally used to analyze images. Then, you will learn modern deep learning methods, such as neural networks and specific models designed for image recognition, and how it can be used to perform more complex tasks like object detection and image segmentation. Additionally, you will learn the creation and impact of AI-generated images and videos, exploring the ethical consideration
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Optimize and Benchmark AI Algorithms for Speed
In this course, you’ll learn how to analyze and benchmark AI-related algorithms so your systems run efficiently at scale. You’ll use computational complexity and data-structure behavior to predict performance as workloads grow, then validate those predictions with small prototype implementations. You’ll learn how to design fair benchmarks, interpret results using metrics like latency, throughput, memory, and scaling curves, and make defensible decisions when trade-offs are unavoidable. By the end, you’ll be able to identify bottlenecks, communicate performance findings clearly, and choose the
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C++: Algorithms
Code and run your first C++ program about algorithms in minutes without installing anything! This course is designed for learners familiar with C++ basics and object-oriented programming. It provides a solid foundation of not just C++, but core data structures and algorithms topics that can be transferred to other languages. The modules in this course cover an introduction to data structures and algorithms, measuring complexity (space and time), algorithm design techniques, and some commonly used algorithms for searching and sorting. To allow for a truly hands-on, self-paced learning experie
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IoT Communications
This course builds on the previous course: IoT Devices. After we have built and programmed a small self-driving vehicle, now it's time get into more advanced territory and enhance the device's connectivity further. To do so you will study radio frequency (RF) communication, the MAC layer, Mesh Networking as well as distributed algorithms for use with geographic locations. These techniques will be applied to your device in the lab, which is composed of four steps, one in each week of the course. In Week 1, after going over some orientation for the course, you will focus on radio frequency (RF)
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Program Structure and Algorithms Part 2
This course will guide you through the essential principles of algorithms and their significance in computational problem-solving. You'll begin by exploring what an algorithm is, its core characteristics, and how it applies to real-world scenarios—from simple everyday tasks to complex computing challenges. As you progress, you will learn about the critical role algorithms play in improving efficiency and scalability across various fields. We’ll break down key concepts such as algorithmic complexity, helping you evaluate the efficiency of different approaches, which will ultimately guide your d
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Employee Attrition Prediction Using Machine Learning
In this project-based course, we will build, train and test a machine learning model to predict employee attrition using features such as employee job satisfaction, distance from work, compensation and performance. We will explore two machine learning algorithms, namely: (1) logistic regression classifier model and (2) Extreme Gradient Boosted Trees (XG-Boost). This project could be effectively applied in any Human Resources department to predict which employees are more likely to quit based on their features. Note: This course works best for learners who are based in the North America regio
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Advanced Intelligent Optimization and its Applications
The second course introduces advanced evolutionary computation methods for intelligent optimization and their applications. This course is built on the Applied AI Foundations Specialization, which introduced the fundamentals of genetic algorithms and particle swarm optimization. In this course, the configuration of intelligent optimization algorithms, handling constraints and multiple objectives, as well as combinatorial optimization, is introduced. Since almost all design problems in science and engineering can be formulated into optimization problems, after this course, you will become a pro
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Python: Logistic Regression & Supervised ML
Build a strong foundation in supervised machine learning by learning how to develop, evaluate, and interpret classification models using Python. In this hands-on course, you will work with the real-world Titanic dataset to explore the complete machine learning workflow, from project setup and data preparation to model evaluation and deployment readiness. You will begin by understanding the lifecycle of a supervised machine learning project, defining problem objectives, and using essential Python libraries such as NumPy and pandas. You will also explore core supervised learning algorithms, inc
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Fundamentals of Orbit Determination
Orbit determination is the process of estimating a spacecraft's trajectory from a set of imperfect tracking observations. It is a foundational component of every spaceflight mission from GPS to Earth-observation satellites to planetary missions like OSIRIS-REx and Mars Reconnaissance Orbiter. This course builds the mathematical machinery on which every orbit-determination process sits: dynamical and measurement models and their partial derivatives, and the representation and propagation of uncertainty. The estimation algorithms themselves (batch least squares, Kalman filtering, smoothing) are
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AI for Medical Diagnosis
AI is transforming the practice of medicine. It’s helping doctors diagnose patients more accurately, make predictions about patients’ future health, and recommend better treatments. As an AI practitioner, you have the opportunity to join in this transformation of modern medicine. If you're already familiar with some of the math and coding behind AI algorithms, and are eager to develop your skills further to tackle challenges in the healthcare industry, then this specialization is for you. No prior medical expertise is required! This program will give you practical experience in applying cutt
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Cyber Security Fundamentals
This course is intended to provide a general introduction to key concepts in cyber security. It is aimed at anyone with a good general knowledge of information and communications technology. The nature, scope and importance of cyber security are explained, and key concepts are justified and explored. This includes examining the types of threat that cyber security must address, as well as the range of mechanisms, both technological and procedural, that can be deployed. The role of cryptography in providing security is explored, including how algorithms and keys play their part in enabling cybe
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YouTube Marketing 2026: YouTube SEO & Algorithms
Created a 99% automated YouTube channel with 3,500,000+ views, generate passive income, grow your personal brand, and generate revenue. I'll give you all the tips that helped me find success on YouTube, and took me a few years to learn and figure out. You will be able to use my advice to create your own winning YouTube channel that helps you achieve your business goals. Sign up for the course, and let's start working on making you successful on YouTube, starting today. RESULTS YOU CAN EXPECT AFTER COMPLETING THIS COURSE By the end of this course, you'll have the skills to grow any chann
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