If you’ve ever been stuck in traffic while your Uber app magically finds a faster route, you’ve already seen the kind of problems Uber engineers solve daily. Every day, Uber makes more real-time decisions than most companies will in a year. Matching riders to drivers, rerouting cars through traffic, and balancing global demand and supply. All of this happens in seconds, billions of times over.
That scale and complexity is what makes Uber such an exciting place to work. Engineers here are not just writing code. They are building optimization systems that move people, food, and goods across thousands of cities in real time. Uber’s interviews are designed to test exactly this problem-solving mindset.
Preparing for such an interview demands a thoughtful approach. But with so many prep lists and guides available online, where should you invest your time: Blind 75, Uber’s Top 75, or the broader LeetCode patterns?
Grokking the Coding Interview Patterns
With thousands of potential questions to account for, preparing for the coding interview can feel like an impossible challenge. Yet with a strategic approach, coding interview prep doesn’t have to take more than a few weeks. Stop drilling endless sets of practice problems, and prepare more efficiently by learning coding interview patterns. This course teaches you the underlying patterns behind common coding interview questions. By learning these essential patterns, you will be able to unpack and answer any problem the right way — just by assessing the problem statement. This approach was created by FAANG hiring managers to help you prepare for the typical rounds of interviews at major tech companies like Apple, Google, Meta, Microsoft, and Amazon. Before long, you will have the skills you need to unlock even the most challenging questions, grok the coding interview, and level up your career with confidence. This course is also available in JavaScript, Python, Go, and C++ — with more coming soon!
In this blog, I’ll compare Blind 75 and Uber Top 75 against the 28 LeetCode patterns from the Grokking the Coding Interview Patterns course. More importantly, I’ll show you how to go beyond lists and develop a prep strategy that helps you recognize patterns the way Uber engineers tackle problems, combining speed, adaptability, and accuracy.
Blind 75 is a curated set of 75 LeetCode problems that cover the most common data structures and algorithms. It has become a go-to resource for many candidates because it removes decision fatigue. Instead of worrying about which problems to practice, you just follow the list. Blind 75 spans essential topics like arrays, strings, linked lists, binary trees, graphs, and dynamic programming.
Uber Top 75 represents the most frequently asked coding problems seen in Uber interviews. These problems give candidates a strong sense of what to expect in the process.
LeetCode patterns are a collection of 28 core problem-solving frameworks that capture the logic behind almost every coding interview question. Instead of focusing on individual problems, they highlight reusable strategies such as sliding window, two pointers, fast and slow pointers, backtracking, dynamic programming, topological sort, and graph traversal. By learning these patterns, you train yourself to recognize the underlying structure of new problems.
Uber is one of the leading tech companies in the world, and while many interview questions may look recycled, the reality is different. With rapid modernization and advancements in technology, Uber naturally faces new engineering challenges. Their interviews often reflect this evolution. With years of hiring experience and the added support of AI tools, it is easier than ever for Uber to design fresh interview questions that go beyond recycled problem sets and truly test how well candidates can adapt.
As a candidate, this means you should be ready for more than just the familiar problems. You may walk into the interview room and face a question that feels entirely new, even if it is built on a pattern you have seen before.
Practicing a static list like Blind 75 can give you a strong starting point, but it might not be enough on its own. To succeed at Uber, you need preparation that equips you to handle the unseen.
Learning LeetCode Patterns can make a big difference in Uber interviews because the company’s coding challenges often mirror real-world problems. Whether it is finding the shortest route across a city, balancing demand and supply, or optimizing schedules, these problems map directly to patterns like graph traversal, heaps, dynamic programming, and sliding windows.
By focusing on patterns, you train yourself to recognize the underlying structure of new problems rather than relying on having seen the exact question before. Preparing through patterns helps you stay confident, even when the problem in front of you feels new.
With 28 coding patterns in total, it’s easy to feel overwhelmed and wonder where to start. To make this easier, I’ve categorized them based on how often they appear in recent Uber coding interviews.
Must-know patterns: These are the backbone of Uber interviews, covering optimization, routing, custom problem-solving, and real-time tracking. If you master these, you’ll be ready for the majority of core challenges.
Very common, high-value patterns: The next group includes patterns that frequently appear in scheduling problems, dependency resolution, connectivity checks, and classic interview staples.
Situational but valuable patterns: These appear less often but can still surface in Uber interviews. They usually involve generating possibilities, ranking results, or specialized data handling. Spending some time here helps you avoid surprises.
Finishing line helpers: A handful of patterns are lower priority for Uber, but still worth practicing if you want well-rounded prep or are also applying to other companies.
While certain patterns appear more frequently in Uber interviews, relying only on those can leave you with weak spots. Building familiarity with the full set ensures that no matter how a question is framed, you’ll have the tools to tackle it.
The key to Uber interview prep is balancing efficiency with breadth. Here’s a four-step plan I recommend:
Start with the overlap: Begin with the problems that appear in both Blind 75 and Uber’s Top 75. This gives you a strong foundation while ensuring your early practice is highly relevant.
Cover Uber-specific questions: Next, move through the remaining Uber Top 75 problems. These will give you a sense of what’s unique to Uber and the types of challenges the company emphasizes.
Complete Blind 75 for broader coverage: Once you are confident with Uber-specific problems, return to Blind 75 to practice the questions not covered by Uber’s list. This ensures you build well-rounded fundamentals.
Strengthen any remaining patterns: Finally, focus on the LeetCode Patterns you haven’t covered yet. This step ensures you are ready for unseen variations and builds the adaptability Uber values in its interviews.
Following this sequence keeps your prep efficient while also ensuring you cover the full range of patterns. As I emphasized earlier in this series, depth matters as much as coverage. Use the same rubric and scoring framework where, for every pattern, you solve one easy problem for 1 point, two medium problems for 4 points each, and one hard problem for 6 points. Reaching the full 420-point benchmark across all 28 patterns will give you the kind of preparation that covers Uber’s interviews and builds lasting confidence.
Beginning with the overlap between Blind 75 and Uber’s Top 75 gives you the highest return on effort. These questions focus on the computer science fundamentals that every candidate should know, while also reflecting the problem areas Uber cares about most. By starting here, you build a solid foundation, save time, and gain confidence knowing that you are practicing problems that truly matter.
Let’s look at Blind 75 and Uber’s Top 75 side by side to understand where they overlap and how much common ground they share.
Blind 75 (Problem Name) | Uber 75 (Problem Name) |
Best Time to Buy and Sell Stock | Best Time to Buy and Sell Stock |
Merge Intervals | Merge Intervals |
Number of Islands | Number of Islands |
Longest Palindromic Substring | Longest Palindromic Substring |
Meeting Rooms II | Meeting Rooms II |
Group Anagrams | Group Anagrams |
Top K Frequent Elements | Top K Frequent Elements |
Alien Dictionary | Alien Dictionary |
Minimum Window Substring | Minimum Window Substring |
Word Search | Word Search |
Coin Change | Coin Change |
Product of Array Except Self | Product of Array Except Self |
Word Break | Word Break |
Serialize and Deserialize Binary Tree | Serialize and Deserialize Binary Tree |
Word Search II | Word Search II |
Find Minimum in Rotated Sorted Array | Find Minimum in Rotated Sorted Array |
Kth Smallest Element in a BST | Kth Smallest Element in a BST |
Insert Interval | Insert Interval |
Two Sum | Bus Routes |
Valid Parentheses | Longest Continuous Subarray With Absolute Diff Less Than or Equal to Limit |
Longest Substring Without Repeating Characters | My Calendar I |
3Sum | Construct Quad Tree |
Merge k Sorted Lists | Squares of a Sorted Array |
Container With Most Water | Number of Islands II |
Spiral Matrix | Rotating the Box |
Maximum Subarray | Course Schedule II |
Climbing Stairs | The Maze |
Rotate Image | The Maze II |
Longest Consecutive Sequence | Maximum Coin Collection |
Merge Two Sorted Lists | Find the Closest Palindrome |
Valid Palindrome | Design Hit Counter |
Course Schedule | Number of Black Blocks |
Jump Game | Evaluate Division |
Find Median from Data Stream | Block Placement Queries |
Search in Rotated Sorted Array | LRU Cache |
Valid Anagram | First Unique Number |
Palindromic Substrings | Shuffle an Array |
House Robber | Largest Rectangle in Histogram |
Binary Tree Maximum Path Sum | Minimum Operations to Write the Letter Y on a Grid |
Set Matrix Zeroes | Text Justification |
Contains Duplicate | Basic Calculator |
Reverse Linked List | Random Pick with Weight |
Longest Repeating Character Replacement | Number of Provinces |
Longest Increasing Subsequence | Cherry Pickup |
Combination Sum | Count Nice Pairs in an Array |
Clone Graph | Maximum Earnings From Taxi |
Remove Nth Node From End of List | Detonate the Maximum Bombs |
Reorder List | Collect Coins in a Tree |
Unique Paths | Number of Adjacent Elements With the Same Color |
Maximum Product Subarray | Valid Sudoku |
Missing Number | Word Ladder |
Sum of Two Integers | Basic Calculator II |
Decode Ways | Reconstruct Itinerary |
Linked List Cycle | Insert Delete GetRandom O(1) |
Lowest Common Ancestor of a Binary Search Tree | Task Scheduler |
Number of Connected Components in an Undirected Graph | 24 Game |
Implement Trie (Prefix Tree) | Open the Lock |
House Robber II | Koko Eating Bananas |
Binary Tree Level Order Traversal | Shortest Bridge |
Longest Common Subsequence | Time Based Key-Value Store |
Non-overlapping Intervals | Subarrays with K Different Integers |
Meeting Rooms | Analyze User Website Visit Pattern |
Pacific Atlantic Water Flow | Minimum Number of Taps to Open to Water a Garden |
Maximum Depth of Binary Tree | Maximum Points You Can Obtain from Cards |
Encode and Decode Strings | Longest Path With Different Adjacent Characters |
Validate Binary Search Tree | Add Two Numbers |
Same Tree | Minimum Path Sum |
Design Add and Search Words Data Structure | Simplify Path |
Construct Binary Tree from Preorder and Inorder Traversal | Dungeon Game |
Invert Binary Tree | Kth Largest Element in an Array |
Reverse Bits | Sliding Window Maximum |
Graph Valid Tree | Walls and Gates |
Counting Bits | Burst Balloons |
Number of 1 Bits | Water and Jug Problem |
Subtree of Another Tree | LFU Cache |
The list above shows that out of Uber’s Top 75 problems, 18 also appear in Blind 75, which is about 24%. This is a good starting point. It gives you momentum early on and sets the stage for the next logical step, i.e., moving into the Uber-specific questions that highlight what makes the company’s interviews unique.
Now, let’s examine the pattern coverage achieved by focusing on the overlapping problems, according to the rubric I’ve established. In the bar chart below, each bar represents a pattern. The length of the bar shows what percent of the full 15 points you’ve earned for that pattern, while the label highlights how many easy, medium, and hard problems went into that score.
The bar chart above shows that you get to practice 13 out of the 28 core patterns, which is about 46% coverage (almost half). That is already a valuable start because each pattern you touch builds familiarity and counts toward your preparation. When measured against the 1–2–1 rubric, the depth is not complete yet. For example, some patterns like Dynamic Programming and Merge Intervals are represented only at the medium level, while others appear only through a hard or an easy problem.
Even though the coverage is partial, this is where the rubric comes in. By deliberately adding the missing easy, medium, and hard questions, you can bring each pattern up to full strength. And remember, simply getting to know a pattern matters. Every bit of exposure makes you more confident when facing new variations in Uber’s interviews.
Working through Uber-specific questions gives you direct insight into the types of challenges the company emphasizes. By practicing these questions, you not only build technical skill but also get familiar with the unique flavor of Uber’s interviews, which boosts both confidence and relevance in your prep.
Let’s look at what new patterns get unlocked when you practice Uber-specific questions.
Pattern |
Two Pointers |
Sliding Window |
Top K Elements |
Modified Binary Search |
Greedy Techniques |
Backtracking |
Dynamic Programming |
Topological Sort |
Tree Depth-first Search |
Knowing What to Track |
Union Find |
Sort and Search |
Matrices |
Stacks |
Graphs |
Tree Breadth-first Search |
Hash Maps |
Custom Data Structures |
Math and Geometry |
The list above shows that you get introduced to 8 new patterns. That is a strong addition, as it takes your total coverage from 13 patterns to 21 out of 28, which is about 75%. This means Uber-specific practice does not just build relevance, it also gives you much broader exposure to the core problem-solving strategies you need.
Now, let’s see how well these Uber-specific patterns meet the coverage criteria set by my rubric. The bar chart below highlights the newly covered patterns in green on the y-axis.
With Uber-specific questions, you deepen coverage for patterns already introduced through the overlap and unlock several new ones. The bar chart above shows that many of these patterns reach strong levels of completion under the rubric, with nine already above 90% coverage, including Dynamic Programming, Graphs, Sliding Window, Matrices, and Custom Data Structures.
A few fall in the partial range, such as Backtracking, Topological Sort, and Tree Breadth-first Search, which means you are gaining exposure but can still add missing easy, medium, or hard problems. Some others, like Top K Elements, Hash Maps, and Sort and Search, remain underrepresented, yet even here the value lies in getting that first layer of familiarity.
Overall, this step takes your preparation much closer to complete coverage and ensures you are practicing the patterns that matter most for Uber interviews.
Working through the remaining Blind 75 problems adds balance to your preparation. These questions may not be Uber-specific, but they strengthen core fundamentals across data structures and algorithms, filling in gaps left by the overlap and Uber Top 75. This broader practice ensures you are not just ready for Uber, but also builds skills that transfer to any technical interview.
Let’s see what patterns we cover by practicing the Blind 75 only questions:
Pattern |
Two Pointers |
Sliding Window |
Merge Intervals |
Modified Binary Search |
Greedy Techniques |
Dynamic Programming |
Topological Sort |
Matrices |
Stacks |
Graphs |
Tree Depth-first Search |
Tree Breadth-first Search |
Trie |
Knowing What to Track |
Union Find |
Fast and Slow Pointers |
In-Place Manipulation of a Linked List |
Heaps |
K-way Merge |
Cyclic Sort |
Bitwise Manipulation |
By practicing the remaining Blind 75 problems, you unlock 6 new patterns, which takes your total coverage to 27 out of 28 patterns, or about 96%. Reaching this milestone is significant because it means you now have exposure to nearly the entire pattern set, giving you both breadth and adaptability for Uber interviews.
Now, let’s see how well these patterns are covered according to the rubric.
The bar chart above shows that many of the most important patterns, such as Dynamic Programming, Graphs, Stacks, and Tree traversals, are fully covered now. Some patterns, like Sliding Window, Matrices, and Graphs, are very close to full coverage.
Several others, including Greedy Techniques, Two Pointers, and Merge Intervals, fall in the partial range, which means you have exposure and only need to add a few more problems for full strength. The remaining handful, like Heaps, K-way Merge, and Cyclic Sort, are underrepresented, but even here, you have started building familiarity. Overall, this milestone shows real breadth and depth, with only one pattern left to reach complete coverage.
The bar chart below clearly shows how well the 28 patterns have been covered so far and which areas still need more attention.
Looking at the overall picture, a good number of patterns are already well covered and close to complete. A few others, such as Modified Binary Search, Heaps, and Hash Maps, still need more attention to reach full strength. Most importantly, there is one pattern, Subsets, that has not been covered by either Blind 75 or Uber’s Top 75, which makes it essential to address separately. Covering this final gap will take your preparation to all 28 patterns and complete the journey.
Here are a few problems to help you cover the Subsets pattern:
Pattern | Easy Problem | Medium Problems | Hard Problem |
Subsets |
|
|
|
Starting with the overlap between Blind 75 and Uber’s Top 75, you already cover 46.4% of the patterns, which is almost half. Adding Uber-specific questions increases the total to 75%, which is huge. Working through the remaining Blind 75 problems takes you even further, raising the total to 96%. That leaves just 3.6%, one final pattern, still outside these sets, which you can tackle separately. Covering that last pattern, Subsets in this case, takes you all the way to 100% coverage across all 28 patterns.
Looking at the score breakdown, you have earned 277 points out of the ideal 420 so far. The overlap between Blind 75 and Uber Top 75 contributed 69 points, while Uber-only problems added the largest share with 153 points. The Blind 75-only set then contributed another 55 points.
This leaves 143 points still on the table, which can be earned by completing the missing easy, medium, and hard problems as per our 1-2-1 rubric across underrepresented patterns. Closing this gap will take you to the full 420-point target and complete your preparation.
Preparing for Uber interviews is not about memorizing a fixed list of problems. It is about building the flexibility to handle new challenges with confidence. Blind 75 gives you a foundation, Uber’s Top 75 brings relevance, and LeetCode patterns give you the adaptability to tackle the unknown.
What matters most is how you bring these pieces together. By focusing on the right patterns, following a structured plan, and aiming for both depth and coverage, you set yourself apart as someone ready to think like an Uber engineer. That is the preparation that will carry you through the interview room and beyond.
Good luck!
While this blog gives you a data-driven way to measure and close your prep gaps, the right learning tools can accelerate your progress even further. Here are two highly effective resources to complement your study plan:
Educative’s personalized interview prep: It’s your tailored prep companion that adapts to your skill level, and focuses on the 28 essential LeetCode patterns we’ve been discussing. You can work on the patterns that need the most attention, track progress with clear metrics, and know exactly what to tackle next. Whether it’s adding an easy problem to build confidence or a hard one to push for mastery, you’ll always be working on the right problems at the right time.
Educative’s mock interviews: Practicing is not just about solving problems. It is also about handling real interview pressure. Educative’s AI mock interviews let you simulate actual interview conditions, get actionable feedback, and improve in areas like problem-solving speed. This way, you are not only technically prepared but also confident and ready to perform under time constraints.
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