Managing Learning Challenges in Programming

𝗜’𝘃𝗲 𝘁𝗿𝗮𝗶𝗻𝗲𝗱 𝟱𝟬+ 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀 — 𝗮𝗻𝗱 𝘁𝗵𝗲𝘆 𝗮𝗹𝗹 𝗺𝗮𝗸𝗲 𝘁𝗵𝗲 𝘀𝗮𝗺𝗲 𝗺𝗶𝘀𝘁𝗮𝗸𝗲. They reread notes. Rewatch tutorials. But rarely 𝘁𝗲𝘀𝘁 what they actually understand. That’s the biggest trap in learning — confusing 𝗳𝗮𝗺𝗶𝗹𝗶𝗮𝗿𝗶𝘁𝘆 with 𝗺𝗮𝘀𝘁𝗲𝗿𝘆. When I was learning my first programming language, I did the same thing — endless repetition, zero retention. Until I discovered Richard Feynman’s principle: “If you can’t explain it simply, you don’t understand it well enough.” That line changed how I learn — and how I teach. Now I use five proven methods that turn learning into a system: 𝗧𝗵𝗲 𝗙𝗲𝘆𝗻𝗺𝗮𝗻 𝗧𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲 — simplify until it’s crystal clear. 𝗔𝗰𝘁𝗶𝘃𝗲 𝗥𝗲𝗰𝗮𝗹𝗹 — test yourself, don’t just reread. 𝗧𝗵𝗲 𝗟𝗲𝗶𝘁𝗻𝗲𝗿 𝗦𝘆𝘀𝘁𝗲𝗺 — repeat less, remember more. 𝗔𝗜 𝗣𝗿𝗼𝗺𝗽𝘁𝘀 — use AI to explain, quiz, and summarize. 𝗧𝗵𝗲 𝗛𝗮𝗿𝘃𝗮𝗿𝗱 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 — spaced repetition, self-testing, and feedback loops. And most importantly — 𝗽𝗿𝗮𝗰𝘁𝗶𝗰𝗲 𝗶𝗺𝗺𝗲𝗱𝗶𝗮𝘁𝗲𝗹𝘆. Real understanding doesn’t happen in your head. It happens in action. Since then, I’ve learned faster — and helped others do the same. Because smart learning isn’t about IQ. It’s about 𝗶𝘁𝗲𝗿𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗽𝗿𝗮𝗰𝘁𝗶𝗰𝗲. 💬 What’s one learning habit you’d change if you could start over? — Natan Mohart

Your most talented software engineers left years ago, and they told their equally talented friends not to apply to your company. It hurts, but this is the impact of not creating a learning culture within your engineering organisation. As a leader, learning and growth needs to be your top priority. Ask your engineers: "what do they like about working here?". If "learning" is not mentioned, you have work to do! Some leaders believe that special days of learning are the way to do it - Hack days, learning days or “work on open source” day. I disagree. Those special days are fine, but it’s not enough. Learning needs to happen every day. Special days carved out for learning are also usually harder to do if you’re a middle or lower level manager. Don’t worry though, there are plenty of easy ways to incorporate learning into the daily job. Here are some methods I’ve used over the years that seemed to have worked well: 1. When you're kicking off something new, or you're thinking about refactoring something, don't just jump into building it. Ask your engineers to take a couple of days and have a go at a new stack, or a new way of doing something. Come back a few days later and compare solutions as a group. 2. Don't pre-assign tasks according to the strengths of a developer's current skill set. That just reinforces and deepens current skills, whilst other developers who've never worked in that stack or codebase will never have the opportunity to learn it. Instead, do the opposite! Assign tasks to the developer with the weakest skills in that space, or, at a minimum, randomize it. Continue to do that and the whole team will uplift together. 3. Create time in the plan to learn, incorporate it into estimations. If you’re doing point 2, you’re going to have the allow time for it because initially the team will slow down. If you're stepping into an unknown area as a team, it's a great learning opportunity! Make the most of it and carve out the right amount of time so that the team has the space to learn. 4. When you need to carve out dedicated time, tie it to a business objective. In point 3 above, those new unknowns are usually from a request to achieve a business outcome. Intentionally tie them together so that the learning achieves the business value. Of course, this means that relationship has to already exist. Your job is to make sure they stay connected and the value is known to stakeholders. 5. “Every day should be a learning day” say it to your team, often. Ask them to hold each other and you to account. Are you living up to that statement? Action things that get in the way of this being reality. 6. Hire growing learners and prioritise it over things like “experience with our stack”. You don’t actually need experience in your stack if you’re a sharp learner. Someone who has mastered the art of learning can be productive in something new in a week. I’m sure I’ve missed plenty of other methods. Share what you’ve seen work in the comments.

Most developers learn fast… but forget even faster. I’ve been there too. You learn a new concept today. It clicks. You feel confident. Two weeks later? You can’t recall half of it. That’s not because you’re bad at learning. It’s because most of us consume content instead of turning it into memory. Good engineers don’t learn more. They learn in a way that actually sticks. Here’s what makes the difference 👇 1. Learn smaller than you think - Don’t say “I’ll learn Java Streams.” - Say, “I’ll understand map vs flatMap with 3 examples.” - Small wins compound. 2. Write before you forget - Put the idea in your own words. - A short note you wrote yourself beats rewatching a 30-minute video. 3. Revisit on purpose - Come back after 1 day → 7 days → 30 days. - This simple habit can double retention. 4. Use it immediately - One tiny program. - One small feature. - One real problem. - Application locks learning in. 5. Explain it out loud - To a friend. - To a teammate. - Or even to a LinkedIn post. - If you can explain it simply, you understand it deeply. 6. Practice recall, not recognition - Close the editor. - Ask yourself: How would I build this from scratch? - That moment of struggle is where real learning happens. 📚 𝗙𝗿𝗲𝗲 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 𝘁𝗼 𝗟𝗲𝗮𝗿𝗻 𝗦𝗺𝗮𝗿𝘁𝗲𝗿 (𝗡𝗼𝘁 𝗛𝗮𝗿𝗱𝗲𝗿) 🔗 Learning How to Learn (Coursera – Free Audit) https://lnkd.in/dWGeCiAb 🔗 Spaced Repetition Explained - https://lnkd.in/dK4tWKUv 🔗 Feynman Technique (Simple Explanation) - https://lnkd.in/dMNkGNdf 🔗 Active Recall for Programmers - https://lnkd.in/dbC3cq4A 🔗 Notes for Developers (FreeCodeCamp) - https://lnkd.in/dMkAyWud Learning fast feels good. Learning in a way that sticks changes your career. If you’re learning something today, make sure future-you can still use it. 𝗚𝗲𝘁 𝘁𝗵𝗲 𝗚𝘂𝗶𝗱𝗲 𝗵𝗲𝗿𝗲 - https://lnkd.in/dauSXK5R Follow Ashish Misal for more insightful content. #Developers #Tips #Programming #Java #Python #SpringBoot #JavaScript

A job searcher wanted to transition into a high-impact data role. However, they faced a clear gap between their current skill set and the industry requirements. While they had foundational knowledge, they struggled with: - Structuring their learning, - Managing their time efficiently, - And aligning their skill development with real-world expectations. They needed a clear and actionable roadmap to bridge the gap between their existing knowledge and their career aspirations. The key challenges included: ⭕ Lack of a structured approach to developing essential meta and technical skills. ⭕ Inefficient time, energy, and emotional management, leading to inconsistent progress. ⭕ Basic SQL knowledge that needed to be advanced to handle industry-level data tasks. ⭕ Uncertainty about how to build and showcase industry-relevant projects. We implemented a 𝗠𝗲𝘁𝗮 𝗦𝗸𝗶𝗹𝗹𝘀 𝗮𝗻𝗱 𝗧𝗲𝗰𝗵 𝗦𝗸𝗶𝗹𝗹𝘀 𝗥𝗼𝗮𝗱𝗺𝗮𝗽 𝘁𝗮𝗶𝗹𝗼𝗿𝗲𝗱 𝘁𝗼 𝘁𝗵𝗲 𝗰𝗹𝗶𝗲𝗻𝘁’𝘀 𝘀𝗽𝗲𝗰𝗶𝗳𝗶𝗰 𝗻𝗲𝗲𝗱𝘀 𝗮𝗻𝗱 𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 𝗹𝗲𝘃𝗲𝗹: 1) Meta skills roadmap - Focused on time, energy, and emotional management to improve consistency and productivity. - Established daily habits for structured learning and self-discipline. - Set up a progress tracking system to measure growth and make necessary adjustments. 2) Tech skills roadmap (if the client had extensive experience, we skipped foundational steps): - Advanced SQL development: Structured learning plan to move from intermediate to advanced proficiency. - Project-based learning: Focused on building projects aligned with real-world scenarios. - Industry-level exposure: Integrated collaboration with tech leads, stakeholders, and project managers. 3) Building industry-ready projects - Developed industry-level projects showcasing problem-solving skills. - Engaged in paid freelancing to gain real-world experience. - Collaborated with a tech lead, stakeholders, and a project manager to simulate real job conditions. Key Takeaways: -> Having a roadmap makes it easier to stay focused and track progress. -> Managing time and energy is just as important as technical skills. -> Daily habits lead to long-term success. -> Real-world projects help build confidence and credibility. -> Working with a team improves collaboration and problem-solving skills. By following a structured Meta and Tech Skills Roadmap, The job searcher effectively bridged the skill gap and positioned themselves for high-value career opportunities. Follow Jaret André to learn how to land the job you will love.

🚀 After putting my 15 months of hard work and dedication I learned these Some points and Improved my mistakes, This is Priceless Learning for me because it is not taught to you in any course, you learn from your mistakes🚱 Dos 🚀 and Don'ts ❌ for DSA Learning Journey 👇 🚀 DO's 1. Set Clear Objectives: Define your goals and objectives in learning DSA. Are you preparing for coding interviews, enhancing your problem-solving skills, or building a strong foundation for software development? 2. Master the Basics: Begin with a thorough understanding of fundamental concepts it's very Important. 3. Practice Regularly: Dedicate consistent time for problem-solving practice. Regular practice is key to building muscle memory and enhancing problem-solving intuition. 4. Problem Variety: Solve a diverse range of problems covering different data structures and algorithmic techniques. This exposes you to various problem-solving strategies. 5. Learn from Others: Study and understand different problem-solving approaches, even if you're able to solve a problem on your own. Learning from others' solutions can broaden your horizons. 6. Debugging Skills: Cultivate strong debugging skills. Analyzing and fixing errors in your code is a crucial part of the learning process. 7. Active Learning Attitude: Participate in coding communities, forums, and discussions. Engaging with others helps you learn alternative solutions and gain new perspectives. 8. Algorithmic Thinking: Focus on understanding the underlying algorithms rather than just memorizing code. This empowers you to adapt solutions to various scenarios. 9. Stay Consistent: DSA learning is a gradual process. Stay committed and patient. Consistency over time yields more fruitful results than sporadic intense sessions. ❌ DON'Ts 1. Don't Rush: DSA is a marathon, not a sprint. Avoid cramming; take time to absorb concepts fully. 2. Avoid Blindly Copying Code: Even if you find a solution online, don't copy-paste without understanding it. You won't learn that way. 3. Don't Fear Challenges: Difficult problems are opportunities, not obstacles. Embrace them to enhance your problem-solving skills. 4. Avoid Neglecting Theory: Don't just focus on solving problems. Understand the theory behind each data structure and algorithm. 5. Don't Compare Progress: Everyone learns at their own pace. Avoid comparing your progress with others; it's counterproductive. 6. Avoid Procrastination: Procrastination is the biggest Enime for your Growth, so try to learn every day doest matter how much time you spend. 7. Don't Underestimate Basic Concepts: Skipping basics can hinder your understanding of advanced topics. Build a strong foundation. 8. Avoid Burnout: Don't overburden yourself with long hours of practice. Balance is key to sustained learning. 9. Don't Ignore Revision: Revision and Pratice are the backbone of your Preparation, so try to maintain both otherwise your entire hard work be a total waste of time and Energy.

The human brain builds new neural pathways in as little as a few focused minutes a day. But without structure, feedback, and accountability, those same pathways weaken just as fast as they’re created. This explains why 𝘀𝗼𝗺𝗲 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀 𝗴𝗲𝘁 𝘀𝘁𝘂𝗰𝗸 𝗼𝗻 𝗮 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗵𝗮𝗺𝘀𝘁𝗲𝗿 𝘄𝗵𝗲𝗲𝗹. Inconsistency becomes the biggest killer of progress. You feel “behind,” get discouraged, and fall out of the habit entirely. 𝗠𝗼𝗺𝗲𝗻𝘁𝘂𝗺 𝗺𝗮𝘁𝘁𝗲𝗿𝘀 𝗺𝗼𝗿𝗲 𝘁𝗵𝗮𝗻 𝘀𝗽𝗲𝗲𝗱. Once it drops, everything feels harder... because it is. So, how do we fix this issue? 𝗕𝘂𝗶𝗹𝗱 𝗮 𝘀𝘆𝘀𝘁𝗲𝗺 𝘁𝗵𝗮𝘁 𝗿𝗲𝗺𝗼𝘃𝗲𝘀 𝗳𝗿𝗶𝗰𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗿𝗲𝘄𝗮𝗿𝗱𝘀 𝗰𝗼𝗻𝘀𝗶𝘀𝘁𝗲𝗻𝗰𝘆. Systems create predictable results; motivation does not. 𝗛𝗲𝗿𝗲 𝗮𝗿𝗲 𝟱 𝗮𝗰𝘁𝗶𝗼𝗻𝗮𝗯𝗹𝗲 𝘀𝘁𝗲𝗽𝘀 𝘁𝗼 𝗵𝗲𝗹𝗽 𝘆𝗼𝘂 𝗴𝗲𝘁 𝘀𝘁𝗮𝗿𝘁𝗲𝗱: 1. 𝗦𝗲𝘁 𝗮 𝗺𝗶𝗻𝗶𝗺𝘂𝗺 𝗱𝗮𝗶𝗹𝘆 𝗰𝗼𝗺𝗺𝗶𝘁𝗺𝗲𝗻𝘁: even 10 minutes keeps the habit alive. 2. 𝗞𝗲𝗲𝗽 𝗮 𝗻𝗼𝘁𝗲𝗯𝗼𝗼𝗸 𝗯𝘆 𝘆𝗼𝘂𝗿 𝗯𝗲𝗱: write down the next task you plan to do - a tutorial, a small feature, fixing some bug, etc. No more guessing what to do next. 3. 𝗧𝗿𝗮𝗰𝗸 𝘆𝗼𝘂𝗿 𝘄𝗶𝗻𝘀: finished lessons, solved bugs, concepts understood. Leave yourself proof of progress. 4. 𝗨𝘀𝗲 𝟭 𝗼𝗿 𝟮 𝗽𝗿𝗼𝗷𝗲𝗰𝘁𝘀 𝗮𝘀 𝘆𝗼𝘂𝗿 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗲𝗻𝗴𝗶𝗻𝗲 (𝘋𝘔 "𝘴𝘪𝘥𝘦 𝘱𝘳𝘰𝘫𝘦𝘤𝘵" 𝘪𝘧 𝘺𝘰𝘶 𝘸𝘢𝘯𝘵 𝘮𝘺 𝘴𝘪𝘥𝘦 𝘱𝘳𝘰𝘫𝘦𝘤𝘵 𝘤𝘩𝘦𝘢𝘵 𝘴𝘩𝘦𝘦𝘵). 5. 𝗚𝗲𝘁 𝗳𝗲𝗲𝗱𝗯𝗮𝗰𝗸: mentors, peers, or code reviews. Find someone with experience to give you feedback on your code Do this and you’ll 𝗿𝗲𝗯𝘂𝗶𝗹𝗱 𝗺𝗼𝗺𝗲𝗻𝘁𝘂𝗺, 𝗯𝗼𝗼𝘀𝘁 𝗰𝗼𝗻𝗳𝗶𝗱𝗲𝗻𝗰𝗲, 𝗮𝗻𝗱 𝘀𝗺𝗼𝗼𝘁𝗵 𝘆𝗼𝘂𝗿 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗰𝘂𝗿𝘃𝗲.

🤔 Why does it feel like I’m stuck after watching hours of coding tutorials? Here's the hard truth: Watching someone code is like watching someone swim. You'll never learn to float by sitting on the beach. 🧠 You don’t become a better programmer by watching. You become one by doing. → If you’re learning web development, are you building websites from scratch? → If you’re learning data science, are you playing with datasets? → If you’re learning software engineering, are you coding small tools? → If you’re learning the fundamentals, are you coding basic challenges? Not sure where to start? Here are some great platforms to find challenges for any programming path:  👩🏾💻LeetCode - For algorithm and coding challenges. https://leetcode.com/ 👩🏾💻 HackerRank - Solve problems and build domain skills. https://lnkd.in/es9Qb3Gc 👩🏾💻 freeCodeCamp - Build projects while learning. https://lnkd.in/euXPmkfx 👩🏾💻Frontend Mentor - Real-world web development challenges https://lnkd.in/eFH9qud6 👩🏾💻 Kaggle - Explore data science competitions. https://www.kaggle.com/ 👩🏾💻 Exercism - Great for language-specific practice https://exercism.org/ 👩🏾💻 Codewars - Fun, gamified learning. https://www.codewars.com/ 👩🏾💻 Edabit - Short, fun coding challenges. https://edabit.com/ Remember: Active learning is more effective than passive learning. A single hour of writing code teaches more than 10 hours of watching tutorials. Tackle challenges, no matter how small. 𝗖𝗼𝗱𝗲. 𝗠𝗮𝗸𝗲 𝗺𝗶𝘀𝘁𝗮𝗸𝗲𝘀. 𝗙𝗶𝘅 𝘁𝗵𝗲𝗺. 𝗥𝗲𝗽𝗲𝗮𝘁. What small project will you start coding today? 💻 What other coding platforms will you recommend? #Programming #Tech #Growth #LearnWithSofiat

🧠 𝐄𝐯𝐞𝐧 𝐚𝐟𝐭𝐞𝐫 4 𝐲𝐞𝐚𝐫𝐬 𝐚𝐭 𝐒𝐃𝐄, 𝐃𝐲𝐧𝐚𝐦𝐢𝐜 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠 𝐬𝐭𝐢𝐥𝐥 𝐦𝐚𝐤𝐞𝐬 𝐦𝐞 𝐬𝐰𝐞𝐚𝐭… But here’s what I learned: It’s OKAY to struggle with certain topics, even as a fresh engineer. When I started my journey at Microsoft, I thought I’d have everything figured out by now. Reality check - some concepts still challenge me, and that’s perfectly normal. The truth about DSA learning: • Everyone has different strengths and weak spots • What clicks for one person might take another person months • Your background doesn’t define your potential • Small town, weak math, average English? So what! Logic and persistence matter more. Here’s my simple roadmap for mastering DSA: Phase 1: Know Yourself • Take honest stock of what confuses you • Don’t compare your day 1 with someone else’s year 3 • Write down specific topics that make you uncomfortable Phase 2: Build Strong Basics • Arrays and strings first (they’re everywhere!) • Master one pattern at a time • Practice explaining solutions in simple words Phase 3: Tackle the Tough Ones • Dynamic Programming (yes, the scary one!) • Break big problems into tiny pieces • Draw it out, don’t just code it out Phase 4: Consistent Practice • 30 minutes daily beats 5 hours once a week • Focus on understanding, not just solving • Celebrate small wins Remember: Every expert was once a beginner who refused to give up. Your journey is unique. Your timeline is yours. Your success story is waiting to be written. What’s that one DSA topic that still challenges you? Drop it in the comments - let’s learn together! P.S. - If you want help creating a personalized learning path based on your specific strengths and areas for improvement, I’m here to guide you through it: https://lnkd.in/gz44hDxm #SoftwareEngineering #DSA #Microsoft #LearningJourney #TechCareer #GrowthMindset

Q: "I studied Graphs a while back and did not revise, and I seem to have lost it all. I'm briefly going through the lectures again to get a gist of the different types of problems. What is your go-to revision strategy?" A: If this resonates, I'm guessing that once you get the "Accepted" verdict for a problem, you immediately move on to the next one. That's why you're not consolidating your learnings. Instead, when you finish a problem, you should do a "post-mortem": reflect on how it went, things you could have done better, and write down takeaways from it. For instance, for graphs, you could write "I wasted too much time converting the edge list to an adjacency list, I should add that snippet to my cheatsheet," or "I forgot to handle the case where the graph is not connected, I need to check for that in the future." In particular: * Maintain a cheat sheet with the most useful code templates and reusable code blocks. For instance, for graphs, you could have: DFS and BFS templates, creating an adjacency list, reconstructing paths from BFS ancestors, looping over connected components, etc. * Maintain a bug list with bugs you tend to repeat. For instance, when constructing adjacency lists, you may have a tendency to add edges in only one direction. With a combination of post-mortems, a cheat sheet (made by yourself), and a bug list, you'll retain knowledge a lot longer and pick it back up faster.

Students don’t fail in programming because it’s hard. They fail because nothing is forcing them to continue. No pressure. No system. No consequence. That’s why motivation doesn’t work. So instead of relying on motivation… Use commitment devices. Here are simple ways to force consistency: Make it public. Post your goal and progress. Find a partner. No coding = both accountable. Set a penalty. Miss a day? Do extra work. Track your streak. Don’t break the chain. Submit something daily. Even 5 lines of code counts. Lock your rewards. No games or Netflix until you code. Here’s the truth: Discipline is unreliable. But systems? They work. If you want to improve in programming, don’t just try harder. Make it harder to quit. That’s how real progress happens.