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.
- Price: $279.99
- Delivery method: eLearning
- DIR Discount: 20%
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Test Prep
52+ Pre Assessment Questions |
52+ Post Assessment Questions |
Features
Why choose TOPTALENT?
- Get assistance every step of the way from our Texas-based team, ensuring your training experience is hassle-free and aligned with your goals.
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- Have confidence in an exceptional 95% approval rating from our students, reflecting outstanding satisfaction with our course content, program support, and overall customer service.
- Benefit from being taught by Professionally Certified Instructors with expertise in their fields and a strong commitment to making sure you learn and succeed.
Outline
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