Daily Dev Progress
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π Documenting my journey in software development. π Coding lessons & notes π» Projects & progress updates 𧩠Problem-solving and DSA π± Learning in public β¨ Ideas, insights, and growth BUILDR-CRV6GG One step closer to becoming a better developer every day
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Welcome back girl π Where have you been? You always say you're back, but then disappear again π
@codedbychera
Welcome back girl π Where have you been? You always say you're back, but then disappear again π
@codedbychera
π Good morning, everyone! β€οΈ Iβm back, and it feels good to be here again! π₯°π
Every new day is another chance to grow, chase your dreams, and become better than yesterday. Never give up! πͺ
Iβve got some exciting news! π₯
Iβm happy to share that Iβve been accepted for a 2-month Python Development Internship at Synent Technologies
Knock knockβ¦ π
Guess whoβs back?
Iβm back! And this channel is coming back to life too.π
+2
π₯ 100 Days on LeetCode! Another milestone in my journey as a Software Engineering student.
π― Day 100 completed. Proud of the progress, but the journey is far from over.
π Keep learning. Keep solving. Keep building.
#LeetCode #100Days #CodingJourney #ProblemSolving #DSA #SoftwareEngineering #Consistency #ASTU #CodebyLidia #Codedbychera
Repost from AAU NEWS
Best Websites for Research, Case
Studies, and Free Learning
π Web Archives & Libraries
https://web.archive.org
https://www.loc.gov/collections/
https://www.bl.uk/subjects/digital-collections
https://www.archives.gov/
https://dp.la/
https://www.wdl.org/
https://www.europeana.eu/
π Academic & Research Databases
https://www.jstor.org/
https://www.ssrn.com/
https://core.ac.uk/
https://www.sciencedirect.com/
https://www.springeropen.com/
https://www.nature.com/
https://journals.sagepub.com/
https://onlinelibrary.wiley.com/
https://www.tandfonline.com/
https://www.researchgate.net/
π Business & Economics
https://hbr.org/
https://wrds-www.wharton.upenn.edu/
https://www.hbs.edu/faculty/research/
https://www.mckinsey.com/featured-insights
https://www.forrester.com/
https://www.gartner.com/en
https://nielseniq.com/global/en/insights/
https://econpapers.repec.org/
https://www.nber.org/
https://www.oecd-ilibrary.org/
https://www.rand.org/
https://www.brookings.edu/
https://www.cfr.org/
π Free Books & Educational Media
https://www.gutenberg.org/
https://openstax.org/
https://www.openculture.com/
https://ocw.mit.edu/
https://publicdomainreview.org/
π§ͺ Science & Health
https://pubmed.ncbi.nlm.nih.gov/
https://www.science.org/
π Research, Policy & Data
https://www.pewresearch.org/
https://www.gallup.com/
https://theconversation.com/
Β©οΈ bighabesha_softwares
Join &Share
π
@AAUNEWS1
Repost from N/a
Heyyy π, this is Nazrawi Ketsela. Iβm a 17 year-old guy passionate about Business, Music, and AI.
On this channel, Iβll be sharing what I find interesting, my personal journey, and topics that I think we should discuss as a community. To be honest, opening a channel wasn't originally my idea at all, but big thanks to @itisnahom and @mikiytaye, Iβm finally doing it! π PARTY POPPER SOUND π
Iβm really excited to launch this Telegram channel and build something genuine that we can call a Community. STAY TUNED!
Repost from N/a
hey it's me Coolio, you might know me from the community hike events i've hosted multiple times. (one coming very soon aswell so join up)
so i ..... deleted my channel by mistake. i was trying to delete a post and instead deleted the whole channel smh.
anyways this is my new channel engdi.
we keep going, we keep growing.
share this around the community and lets keep the momentum going β€οΈ
@CoolioCodes
Repost from N/a
Good morning everyone π«‘π«‘
Have a productive Thursday β¨πβ¨
Repost from Negasa Reta | Software Eng.
Book Recommendation: Designing Data-Intensive Applications
I highly recommend reading Designing Data-Intensive Applications by Martin Kleppmann. It is one of the definitive guides for understanding how modern, scalable, and reliable backend systems are built. The book brilliantly breaks down complex concepts like database internals, distributed systems, consensus algorithms, and stream processing into practical, actionable insights. Whether you are designing robust APIs or scaling data pipelines, this is an essential read.
