The Self-Taught Computer Scientist: The Beginner’s Guide to Data Structures & Algorithms

Enhance your programming skills with The Self-Taught Computer Scientist: The Beginner’s Guide to Data Structures & Algorithms course. Master computer science, data structures, and algorithms to solve complex problems and propel your career to new heights. Start a transformative learning journey with real-life examples that yield tangible outcomes. It contains interactive lessons, quizzes, and hands-on labs to build and iterate on your code like a software developer.

Lessons

19+ Lessons | 104+ Exercises | 100+ Quizzes | 154+ Flashcards | 154+ Glossary of terms

TestPrep

52+ Pre Assessment Questions | 52+ Post Assessment Questions 

Lessons 1: Introduction

• What You Will Learn
• Who Is This Course For?
• Self-Taught Success Stories
• Getting Started
• Sticking with It

Lessons 2: What Is an Algorithm

• Analyzing Algorithms
• Constant Time
• Logarithmic Time
• Linear Time
• Log-Linear Time
• Quadratic Time
• Cubic Time
• Exponential Time
• Best-Case vs. Worst-Case Complexity
• Space Complexity
• Why Is This Important?
• Challenge

Lessons 3: Recursion

• When to Use Recursion
• Challenge

Lessons 4: Search Algorithms

• Linear Search
• When to Use a Linear Search
• Binary Search
• When to Use a Binary Search
• Searching for Characters
• Challenge

Lessons 5: Sorting Algorithms

• Bubble Sort
• When to Use Bubble Sort
• Insertion Sort
• When to Use Insertion Sort
• Merge Sort
• When to Use Merge Sort
• Sorting Algorithms in Python
• Challenge

Lessons 6: String Algorithms

• Anagram Detection
• Palindrome Detection
• Last Digit
• Caesar Cipher
• Challenge

Lessons 7: Math

• Binary
• Bitwise Operators
• FizzBuzz
• Greatest Common Factor
• Euclid's Algorithm
• Primes
• Challenge

Lessons 8: Self-Taught Inspiration: Margaret Hamilton

Lessons 9: What Is a Data Structure

• Data Structure and its Types
• Challenge

Lessons 10: Arrays

• Array Performance
• Creating an Array
• Moving Zeros
• Combining Two Lists
• Finding the Duplicates in a List
• Finding the Intersection of Two Lists
• Challenge

Lessons 11: Linked Lists

• Linked List Performance
• Create a Linked List
• Search a Linked List
• Removing a Node from a Linked List
• Finding a Linked List Cycle
• Challenges

Lessons 12: Stacks

• When to Use Stacks
• Creating a Stack
• Using Stacks to Reverse Strings
• Min Stack
• Stacked Parentheses
• Challenges

Lessons 13: Queues

• When to Use Queues
• Creating a Queue
• Python's Built-In Queue Class
• Create a Queue Using Two Stacks
• Challenge

Lessons 14: Hash Tables

• When to Use Hash Tables
• Characters in a String
• Two Sum
• Challenge

Lessons 15: Binary Trees

• When to Use Trees
• Creating a Binary Tree
• Breadth-First Tree Traversal
• More Tree Traversals
• Invert a Binary Tree
• Challenges

Lessons 16: Binary Heaps

• When to Use Heaps
• Creating a Heap
• Connecting Ropes with Minimal Cost
• Challenge

Lessons 17: Graphs

• When to Use Graphs
• Creating a Graph
• Dijkstra's Algorithm
• Challenge

Lessons 18: Self-Taught Inspiration: Elon Musk

Lessons 19: Next Steps

• What’s Next?
• Climbing the Freelance Ladder
• How to Get an Interview
• How to Prepare for a Technical Interview
• Additional Resources
• Final Thoughts

Hands-on LAB Activities (Performance Labs)

What Is an Algorithm

• Iterating Through a List

Recursion

• Printing the Numbers Recursively
• Calculating the Factorial of a Number Recursively

Search Algorithms

• Performing a Linear Search
• Performing a Binary Search

Sorting Algorithms

• Using a Bubble Sort Algorithm
• Using an Insertion Sort Algorithm

String Algorithms

• Determining Anagrams
• Determining a Palindrome

Math

• Implementing FizzBuzz
• Finding the Greatest Common Factor of Two Numbers
• Determining a Prime Number

Arrays

• Locating All the Zeros to the End of a List
• Combining Two Lists

Linked Lists

• Creating a Linked List
• Finding a Linked List Cycle

Stacks

• Tracking Stack's Biggest Number
• Using Stacked Parentheses

Queues

• Creating a Queue Using Two Stacks

Hash Tables

• Removing All Duplicate Words
• Counting All the Characters in a String

Binary Trees

• Using a Breadth-First Search
• Inverting a Binary Tree

Binary Heaps

• Creating a Heap

Graphs

• Implementing Dijkstra's Algorithm