ALGO.AE1
Algorithms For Beginners
Discover the fundamentals of Data Structure and Algorithms for upgrading your problem-solving skills.
- Practice in 33 Hands-On Labs — nothing to install
- 23 Interactive Lessons and 89 topics mapped to the official exam objectives
Beginner Self-paced · 1 year access
33 Hands-On LiveLabs
Practice real IT tasks in guided environments.
- Real environments
- Auto-graded
- No installation
23Interactive Lessons
89Topics
33LiveLab
116Flashcards
116Glossary of terms
01 / Skills you'll get
What you will be able to do
This is a basic Algorithms for beginner’s course that teaches you the fundamentals to design, analyze, and implement effective algorithm techniques for solving real-world problems. Explore the core algorithmic concepts including sorting techniques, mapping time-complexities and resolving issues in a systematic manner. Learn about different types of algorithms, and how to analyze and implement them using Python. Additionally, this beginner’s guide to Algorithms is equipped with interactive lessons, hands-on exercises, and practical assignments that enable the learners to practice their knowledge for enhanced learning and better skill development.
- Create algorithms to solve computational problems
- Design, analyze, and implement efficient algorithms
- Utilize data structures like arrays, linked lists, stacks, queues, trees, graphs
- Ability to present and manipulate data effectively
- Skilled in Python programming
- Understanding of Python syntax, control flow, functions, and object-oriented programming concepts
- Expertise in identifying and resolving problems systematically
Course Highlights
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23 Structured Lessons Comprehensive coverage of core course objectives
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33 Hands-On LiveLabs Interactive guided scenarios with instant evaluation
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1 Year Full Access Self-paced learning accessible anytime on all devices
02 / Lessons & labs
See exactly what you will learn and practice
Lessons
23 Interactive Lessons · 89 topics01 Introduction 4 topics +
- About This Course
- False Assumptions
- Icons Used in This Course
- Where to Go from Here
02 Introducing Algorithms 4 topics +
- Describing Algorithms
- Using Computers to Solve Problems
- Distinguishing between Issues and Solutions
- Structuring Data to Obtain a Solution
03 Considering Algorithm Design 5 topics +
- Starting to Solve a Problem
- Dividing and Conquering
- Learning that Greed Can Be Good
- Computing Costs and Following Heuristics
- Evaluating Algorithms
04 Working with Google Colab 6 topics +
- Defining Google Colab
- Working with Notebooks
- Performing Common Tasks
- Using Hardware Acceleration
- Executing the Code
- Getting Help
05 Performing Essential Data Manipulations Using Python 4 topics · 4 LiveLab +
- Performing Calculations Using Vectors and Matrixes
- Creating Combinations the Right Way
- Getting the Desired Results Using Recursion
- Performing Tasks More Quickly
4 LiveLab in this lesson — see the labs panel →
06 Developing a Matrix Computation Class 4 topics · 2 LiveLab +
- Avoiding the Use of NumPy
- Understanding Why Using a Class is Important
- Building the Basic Class
- Manipulating the Matrix
2 LiveLab in this lesson — see the labs panel →
07 Structuring Data 4 topics · 3 LiveLab +
- Determining the Need for Structure
- Stacking and Piling Data in Order
- Working with Trees
- Representing Relations in a Graph
3 LiveLab in this lesson — see the labs panel →
08 Arranging and Searching Data 3 topics · 3 LiveLab +
- Sorting Data Using Merge Sort and Quick Sort
- Using Search Trees and the Heap
- Relying on Hashing
3 LiveLab in this lesson — see the labs panel →
09 Understanding Graph Basics 4 topics · 3 LiveLab +
- Explaining the Importance of Networks
- Defining How to Draw a Graph
- Measuring Graph Functionality
- Putting a Graph in Numeric Format
3 LiveLab in this lesson — see the labs panel →
10 Reconnecting the Dots 4 topics · 3 LiveLab +
- Traversing a Graph Efficiently
- Sorting the Graph Elements
- Reducing to a Minimum Spanning Tree
- Finding the Shortest Route
3 LiveLab in this lesson — see the labs panel →
11 Discovering Graph Secrets 2 topics +
- Envisioning Social Networks as Graphs
- Navigating a Graph
12 Getting the Right Web page 4 topics · 1 LiveLab +
- Finding the World in a Search Engine
- Explaining the PageRank Algorithm
- Implementing PageRank
- Going Beyond the PageRank Paradigm
1 LiveLab in this lesson — see the labs panel →
13 Managing Big Data 3 topics · 1 LiveLab +
- Transforming Power into Data
- Streaming Flows of Data
- Sketching an Answer from Stream Data
1 LiveLab in this lesson — see the labs panel →
14 Parallelizing Operations 2 topics · 2 LiveLab +
- Managing Immense Amounts of Data
- Working Out Algorithms for MapReduce
2 LiveLab in this lesson — see the labs panel →
15 Compressing and Concealing Data 2 topics · 2 LiveLab +
- Making Data Smaller
- Hiding Your Secrets with Cryptography
2 LiveLab in this lesson — see the labs panel →
16 Working with Greedy Algorithms 2 topics · 1 LiveLab +
- Deciding When It Is Better to Be Greedy
- Finding Out How Greedy Can Be Useful
1 LiveLab in this lesson — see the labs panel →
17 Relying on Dynamic Programming 2 topics · 2 LiveLab +
- Explaining Dynamic Programming
- Discovering the Best Dynamic Recipes
2 LiveLab in this lesson — see the labs panel →
18 Using Randomized Algorithms 2 topics · 4 LiveLab +
- Defining How Randomization Works
- Putting Randomness into your Logic
4 LiveLab in this lesson — see the labs panel →
19 Performing Local Search 3 topics +
- Understanding Local Search
- Presenting Local Search Tricks
- Solving Satisfiability of Boolean Circuits
20 Employing Linear Programming 2 topics · 1 LiveLab +
- Using Linear Functions as a Tool
- Using Linear Programming in Practice
1 LiveLab in this lesson — see the labs panel →
21 Considering Heuristics 3 topics · 1 LiveLab +
- Differentiating Heuristics
- Routing Robots Using Heuristics
- Explaining Path Finding Algorithms
1 LiveLab in this lesson — see the labs panel →
22 Ten Algorithms That Are Changing the World 10 topics +
- Using Sort Routines
- Looking for Things with Search Routines
- Shaking Things Up with Random Numbers
- Performing Data Compression
- Keeping Data Secret
- Changing the Data Domain
- Analyzing Links
- Spotting Data Patterns
- Dealing with Automation and Automatic Responses
- Creating Unique Identifiers
23 Ten Algorithmic Problems Yet to Solve 10 topics +
- Solving Problems Quickly
- Solving 3SUM Problems More Efficiently
- Making Matrix Multiplication Faster
- Determining Whether an Application Will End
- Creating and Using One-Way Functions
- Multiplying Really Large Numbers
- Dividing a Resource Equally
- Reducing Edit Distance Calculation Time
- Playing the Parity Game
- Understanding Spatial Issues
Hands-On Labs Our edge
33 LiveLabs- Performing Logical Operations
- Using Comparison Operators
- Performing Data Manipulations
- Finding the Factorial of a Number Using Recursion
- Using Matrix Operations
- Flattening a Matrix
- Dealing with Missing Values
- Removing the Duplicate Records
- Creating and Traversing a Binary Tree
- Implementing Quick Sort
- Implementing Merge Sort
- Building and Searching a Binary Heap
- Implementing a Graph
- Adding a Graph to a Matrix
- Using Sparse Representations
- Creating a Minimum Spanning Tree
- Adding a Negative Edge to a Graph
- Using the Floyd-Warshall Algorithm
- Creating a Network with a Spider Trap
- Demonstrating the Bloom Filter
- Using the lambda Function
- Setting up a MapReduce Simulation
- Using Compression
- Using Encryption
- Using the change Function
- Printing a Fibonacci Sequence Using Recursion
- Using Dynamic Programming
- Creating a Histogram
- Creating a Monte Carlo Simulation
- Implementing the Quick Select Algorithm
- Computing the Median of a Series
- Visualizing Data Using Python Plotting Functions
- Creating a Maze
Labs run in your browser — nothing to install.
03 / FAQs
Questions before you start
Do I need any prior experience for learning basic Algorithms?+
It is a beginner-friendly course that does not really need any prior experience. However, it is recommended to have basic programming skills in Python and knowledge of fundamental data structures and algorithms concepts for fast learning.
What is the use of Algorithms in Programming?+
Algorithms are the basis of programming that provide a step-by-step structure to resolve a problem or achieve a specified task. It is an essential tool for programmers as it helps them to create a systematic approach, improve code efficiency, and enable the development of complex software applications.
Should I learn Algorithms along with Data Structure as a beginner?+
Absolutely Yes! Learning Algorithms and Data Structure is totally worth your time and investment as a beginner. Both the courses go hand-in-hand. Algorithms usually depend on specific data structures for storing and manipulation. Additionally, this will also give you a solid foundation for learning advanced-level courses on machine learning, artificial intelligence, and systems design.
Which programming language will I learn in this course?+
You’ll learn Python in this beginner’s Algorithms course.
Who is this course best suited for?+
This course is ideal for all those wanting to learn Data Structure and Algorithms, one of the most sought-after skills in IT. Especially those in the field of computer science, software development, data science, research, and problem-solving will benefit greatly from this course.
Keep going
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Upgrade Your Problem-Solving Skills
Learn Data Structure and Algorithms to develop a system approach and excel in the software development field
- 1 year of full access
- 33 LiveLab included
- Certificate of completion