English | MP4 | AVC 1920×1080 | AAC 44KHz 2ch | 123 Lessons (13h 49m) | 3.87 GB
Take a unique Python course that will help you master data structures and algorithms, allowing you to confidently handle any tasks in a technical interview. You will gain knowledge that will make you a professional in algorithms and prepare you for interviews at the largest IT companies.
What to expect:
- Learning key patterns for solving any interview tasks.
- Systematic knowledge to become a true master of technical interviews.
- Practical advice and a ready-to-use training program based on a proven methodology.
This course is created by a developer who went from fearing tasks to being confident in their abilities. “Algo University” combines hundreds of resources, books, articles, and courses into one complete program that will eliminate your uncertainty.
You will master:
- The most important topics of data structures and algorithms.
- Methodologies for applying knowledge to solve real problems.
- Practical exercises for interview preparation.
Result:
Upon completing the course, you will be able to confidently solve any interview tasks, increase your chances of employment at leading companies, and clear the path to a high-paying developer career.
This course is for you if:
- You are a beginner programmer struggling to progress due to a lack of a clear learning plan.
- You feel you lack the skills to pass interviews but are serious about learning everything necessary.
- You cannot or do not want to spend $40,000+ on a computer science degree but are ready to move forward in your career.
- You do not want to study unnecessary theory that is not useful for employment and only wastes your time.
- You want to learn only truly important topics in a simple and understandable way.
This course is not for you if:
- You are only looking for theoretical information and are not ready for practical tasks.
- You are not ready to invest in yourself and prefer the cheapest ways of learning.
- You are not ready to work hard – to achieve results, you will need to watch all the lessons and solve 50-100 practical tasks.
- You are not interested in becoming an excellent programmer or working in large tech companies. If this is the case, this course may not be suitable for you.
Table of Contents
1 Why every developer needs to learn Data Structures & Algorithms
2 Introduction to Data Structures
3 Introduction to Algorithms
4 How to MASTER Data Structures & Algorithms
5 How to Solve Coding Problems – My 6-Step Framework
6 Applying the framework TwoSum
7 What this Bonus Module is about
8 Writing Our First Python Program
9 Python variables (Building Block 1)
10 Errors (when things go wrong…)
11 Basic Python datatypes – (Building Block 2)
12 Basic Python datatypes 2
13 Making our datatypes more POWERFUL – Methods
14 Python Functions (Building Block 3)
15 The flow of a program (Building Block 4)
16 Compound data types
17 Error handling – how to prevent crashes..
18 Libraries – standing on the shoulders of giants
19 Modeling the real world using code – Object-Oriented Programming Introduction
20 OOP-1 – Classes & Objects – Let’s make some cookies!
21 OOP-2 Objects & Classes in Python – I have been lying to you.
22 OOP-3 Creating our Own Classes
23 OOP-4 Creating our Own Classes 2
24 OOP-5 Private attributes & Properties Creating Secrets (Advanced)
25 Module Overview – How do developers analyze algorithms
26 Introduction to Efficiency
27 Big O notation – What makes an algorithm fast
28 Good vs bad runtime – O(n) & O(n^2)
29 Best runtime – O(1)
30 Logarithmic & linearithmic time complexityO(logn) & O(nlogn)
31 (Advanced) Terrible Time Complexities! – O(2^n), O(n!) and beyond
32 Multiple inputs
33 Space complexity
34 Data Structures Introduction
35 The Computer’s Memory
36 ListsArrays 1
37 ListsArrays 2 – Big O
38 (advanced) Dynamic Lists & list memory allocation
39 List Exercise 1 walkthrough
40 List exercise 2 walkthrough
41 Linked Lists Introduction – What is a Linked List
42 Linked Lists Implementation in Python 1
43 Linked List implementation in Python 2
44 Linked List Big O
45 List vs Linked List
46 Linked List Exercise 1 Reverse a Linked List
47 Linked List Exercise 2 Palindrome
48 Stacks & Queues Introduction
49 Stacks & Queues in Memory
50 Stack Implementation in Python
51 Queue Implementation in Python
52 Stacks Big O
53 Queue Big O
54 Stack exercise walkthrough
55 Queue exercise walkthrough
56 Trees Introduction
57 Binary Search Trees
58 Binary Search Tree Implementation 1 – Insertion
59 Binary Search Tree Implementation 2 – Searching
60 Binary Search Tree Implementation 3 – Deletion
61 Heaps
62 Heap Implementation 1
63 Heap Implementation 2
64 Graphs Introduction
65 Undirected Graph Implementation
66 Different Types of Graphs
67 Directed Graph Implementation
68 Weighted (Directed) Graph Implementation
69 Hash Maps Introduction
70 Hash Maps Behind the Scenes
71 Hash Maps Big O
72 Hash Map Implementation from First Principles
73 Hash Map Exercise Walkthrough
74 Algorithms introduction
75 List Algorithms
76 Recursion introduction
77 The Call Stack & Stack Overflow
78 How to use recursion (step-by-step)
79 Recursion exercise 1 walkthrough – Fibonacci
80 Recursion exercise 2 walkthrough – Palindrome
81 Recursive vs iterative programming
82 Sorting introduction
83 Insertion Sort
84 Insertion Sort Implementation
85 Bubble Sort
86 Bubble Sort Implementation
87 Merge Sort
88 Merge Sort Implementation
89 Quick Sort
90 Quick Sort Implementation
91 Which sorting algorithm should you use
92 Graph Searching Introduction
93 Breadth-First Search (BFS)
94 BFS Implementation
95 Depth-First Search (DFS)
96 DFS Implementation
97 DFS vs BFS
98 Dijkstra’s Algorithm
99 Dijkstra’s Algorithm Implementation
100 Dynamic Programming Introduction
101 Dynamic programming exercise walkthrough Fibonacci
102 When To Use Dynamic Programming (My Framework)
103 Dynamic programming practical examples from my startup
104 Two Pointers
105 Two Pointers 2
106 Two Pointers 3
107 Sliding Window
108 Sliding Window 2
109 Fast and Slow Pointers (Tortoise and Hare)
110 Fast and Slow Pointers 2
111 Fast and Slow Pointers 3
112 Backtracking
113 Backtracking 2
114 Divide and Conquer
115 Divide and Conquer 2
116 Prefix sum
117 Prefix sum 2
118 Prefix sum 3
119 Note on this module
120 How to Apply for Jobs and Get More Interviews
121 How to Leverage LinkedIn to Get Interviews
122 The Top Non-Technical Skills to get Hired
123 How to Crack the Coding Interview
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