3 answers
3 answers
Updated
Joseph’s Answer
To be a good software engineer, you need to know how to use your tools well every day. If you want to work with data structures, a strong math background is important, especially in fields like Generative AI, which handle big data sets to get results.
AI isn't just about mysterious models; these models need well-organized data to work.
In Generative AI, text or images are turned into complex vectors. To manage these, you need special data structures like k-d trees or graphs for finding similar items, like the closest match to a given input.
The "T" in ChatGPT stands for Transformer. This system uses stacks and queues to control the order of tasks and manage how attention moves across words in a sequence.
Handling large language models requires knowing hash tables and heaps. This knowledge helps keep data retrieval fast, so response times don't get too slow.
Alison.com course "Applied Math: Practical Machine Learning with TensorFlow" if you want to see the math in action using code, this course bridges the theory with Google’s AI framework.
AI isn't just about mysterious models; these models need well-organized data to work.
In Generative AI, text or images are turned into complex vectors. To manage these, you need special data structures like k-d trees or graphs for finding similar items, like the closest match to a given input.
The "T" in ChatGPT stands for Transformer. This system uses stacks and queues to control the order of tasks and manage how attention moves across words in a sequence.
Handling large language models requires knowing hash tables and heaps. This knowledge helps keep data retrieval fast, so response times don't get too slow.
Joseph recommends the following next steps:
Updated
semi’s Answer
Master the fundamentals first: core programming concepts, clean code, and basic system knowledge. Build small, real projects consistently.
Practice arrays, strings, linked lists, stacks, queues, hash maps, trees, graphs, recursion, sorting, searching, and basic dynamic programming.
For technical interviews, practice timed problems and explain your thinking clearly. For behavioral rounds, prepare real stories about teamwork, challenges, and learning from mistakes. Communication is as important as code.
Practice arrays, strings, linked lists, stacks, queues, hash maps, trees, graphs, recursion, sorting, searching, and basic dynamic programming.
For technical interviews, practice timed problems and explain your thinking clearly. For behavioral rounds, prepare real stories about teamwork, challenges, and learning from mistakes. Communication is as important as code.
Updated
Chinyere’s Answer
Hi Benito!
That’s a great question! You already have an advantage because you are considering this already.
First, concentrate on the fundamental data structures that are most often seen in interviews and practical work: arrays, linked lists, stacks, queues, hash tables (which are important), trees (particularly binary trees and binary search trees), heaps, and graphs. You should also know how to sort, search, recur, and understand time and space complexity (Big O). Practice justifying the effectiveness of your solution and why it works rather than merely memorizing it.
Second, practice problem-solving aloud for technical interviews. Make use of resources such as CodeSignal, HackerRank, or LeetCode. Set a timeframe, describe your reasoning in detail, and develop clean code to mimic actual interview settings. If you're targeting larger organizations, go over the fundamentals of system architecture as well. Gain a high-level understanding of how databases, scalable systems, and APIs operate.
Third, use the STAR approach (Situation, Task, Action, Result) to create organized narratives for behavioral interviews. Prepare to discuss:
- A challenge you faced
- A time you worked in a team
- A mistake you made and what you learned
- A project you’re proud of
Interviewers are assessing more than just technical skills; they are also looking at communication, teamwork, ownership, and growth mindset.
Put more effort into creating actual projects than interviews. Make applications, add to open source, or construct anything that addresses a practical need. Projects add a unique touch to your career and show ambition.
Maintaining consistency in your problem-solving techniques, quality projects, and communication abilities will put you in a very strong position. Software engineering is more about careful preparation and persistence than it is about being a genius. You’ve got this.
Best wishes!
That’s a great question! You already have an advantage because you are considering this already.
First, concentrate on the fundamental data structures that are most often seen in interviews and practical work: arrays, linked lists, stacks, queues, hash tables (which are important), trees (particularly binary trees and binary search trees), heaps, and graphs. You should also know how to sort, search, recur, and understand time and space complexity (Big O). Practice justifying the effectiveness of your solution and why it works rather than merely memorizing it.
Second, practice problem-solving aloud for technical interviews. Make use of resources such as CodeSignal, HackerRank, or LeetCode. Set a timeframe, describe your reasoning in detail, and develop clean code to mimic actual interview settings. If you're targeting larger organizations, go over the fundamentals of system architecture as well. Gain a high-level understanding of how databases, scalable systems, and APIs operate.
Third, use the STAR approach (Situation, Task, Action, Result) to create organized narratives for behavioral interviews. Prepare to discuss:
- A challenge you faced
- A time you worked in a team
- A mistake you made and what you learned
- A project you’re proud of
Interviewers are assessing more than just technical skills; they are also looking at communication, teamwork, ownership, and growth mindset.
Put more effort into creating actual projects than interviews. Make applications, add to open source, or construct anything that addresses a practical need. Projects add a unique touch to your career and show ambition.
Maintaining consistency in your problem-solving techniques, quality projects, and communication abilities will put you in a very strong position. Software engineering is more about careful preparation and persistence than it is about being a genius. You’ve got this.
Best wishes!