`REMOTE JOB`

📢Role: Developer Advocate

🏪 Company: SerpApi
📍Location: Remote (Global)
👔 Experience Years: Not stated
💸 Salary: 100K – 125K a year + profit share
⏰ Employment Type: Full-time

📌How to Apply:
Send us your resume at careers@serpapi.com

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Focus !!

As an app developer, there are important things you need to add before uploading your app to the store, whether the customer requests it or not.
The most important things you should add are:

1. A notification feature. This is a free service from Firebase. With this service, you can notify users of any changes or new developments in the app.

2. A forced update service: This forces the user to update the app in the event of, for example, problems or vulnerabilities, and a new update is released. The user is prompted to update the app, otherwise they cannot use it. There are several ways to implement this feature.

3. Adding a crash and bug tracking feature to the app (crashlytics). This is also a free service from Firebase. If an error or malfunction occurs in the app, an email notification is sent to you, explaining the error and its location.

This makes it easier for you to discover and pinpoint the exact location of the problem and address it easily.

Mobile UI UX: t.me/mobiledevresourcestp/151

Kotlin Multiplatform: t.me/mobiledevresourcestp/145

Native vs. Cross-Platform Mobile Dev: t.me/mobiledevresourcestp/153

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PAKISTAN🇵🇰 foodpanda is Hiring

Data Analyst (Quick Commerce & Partnerships)

Organization: FOODPANDA
📍Location: Karachi, Pakistan

How To Apply:
jobs.smartrecruiters.com/DeliveryHero/744000151531609-data-analyst-quick-commerce-partnerships-

Telegram Channel👇
t.me/jobsourceglobal

WhatsApp Channel👇
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Finally we got a SaaS that does Nothing

If you’re not using AI, you’re training yourself for a world that no longer exists.

Please😂

🚨FULLY FUNDED SCHOLARSHIP ALERT

🎓Apply for the Fully Funded 2027 UGHE Mastercard Foundation Scholars Program

Key Deadlines & Next Steps
• Application Deadline:October 25, 2026
• Program Start:2027 Academic Year

Application Details Here 👉 https://kenyatrends.co.ke/opportunities/apply-for-the-fully-funded-2027-ughe-mastercard-foundation-scholars-program/

There is something rewarding about grappling with yourself to attain what you are striving for.

Blame AI

Write the definition of done

I recently became familiar with the concept of «definition of done». It is a precise statement of a task that can be checked off to see if the task is complete. In my experience, this is most often a list that you can go through before submitting the task. This is something I've used before... If storing everything in your head counts.

Example: we need a product detail screen. The definition of done for it might be this:

— On this screen we can:
— View all information about the product;
— Add the product to favorites, to cart, share this page with others through third-party apps;
— Rate the product and write a comment;
— We've updated the documentation;
— The screen adapts to phone/tablet layout.

It is important not to confuse the definition of done with the terms of reference. That is the technical explanation of how the "share" screen opens or what we make API requests through. The definition of done rather describes the behavior of the application or related changes, such as updating the documentation.

It's somewhat similar to user stories. But while stories describe everything from a business perspective (who the user is, what they want to do and why), the definition of done refers to a specific task with specific conditions. After all, large tasks can be decomposed and for each decomposed task we can also write its own definition of done.

Unlimited Tech Resources Here 👉 t.me/techpsyche

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Hello World

REMOTE JOB

📢Role: Software engineer

🏪 Company: Sticker Mule
📍Location: Remote (Global)
👔 Experience Years: Not stated
💸 Salary: $150K – $250K yearly + $20k signing bonus
⏰ Employment Type: Full-time

📌How to Apply:
jobs.ashbyhq.com/stickermule/6db27241-e2d4-4f35-a2c4-b58d84621843

Telegram Channel👇
t.me/remotejobskt

WhatsApp Channel👇
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All the Best🥳

Junior Developer:
- Doesn't know Regex
- Doesn't know how to test code programmatically
- Doesn't know how to write good technical stories

Mid Level Developer:
- Doesn't know Regex
- Begins to understand how to test code programmatically
- Begins to understand how to write good technical stories

Senior Developer:
- Doesn't know Regex
- Understands how to test code programmatically
- Understands how to write good technical stories

Feels like magic

✅𝟓-𝐒𝐭𝐞𝐩 𝐑𝐨𝐚𝐝𝐦𝐚𝐩 𝐭𝐨 𝐒𝐰𝐢𝐭𝐜𝐡 𝐢𝐧𝐭𝐨 𝐭𝐡𝐞 𝐃𝐚𝐭𝐚 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 𝐅𝐢𝐞𝐥𝐝✅

💁‍♀️𝐁𝐮𝐢𝐥𝐝 𝐊𝐞𝐲 𝐒𝐤𝐢𝐥𝐥𝐬: Focus on core skills—Excel, SQL, Power BI, and Python.

💁‍♀️𝐇𝐚𝐧𝐝𝐬-𝐎𝐧 𝐏𝐫𝐨𝐣𝐞𝐜𝐭𝐬: Apply your skills to real-world data sets. Projects like sales analysis or customer segmentation show your practical experience. You can find projects on Youtube.

💁‍♀️𝐅𝐢𝐧𝐝 𝐚 𝐌𝐞𝐧𝐭𝐨𝐫: Connect with someone experienced in data analytics for guidance(like me 😅). They can provide valuable insights, feedback, and keep you on track.

💁‍♀️𝐂𝐫𝐞𝐚𝐭𝐞 𝐏𝐨𝐫𝐭𝐟𝐨𝐥𝐢𝐨: Compile your projects in a portfolio or on GitHub. A solid portfolio catches a recruiter’s eye.

💁‍♀️𝐏𝐫𝐚𝐜𝐭𝐢𝐜𝐞 𝐟𝐨𝐫 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰𝐬: Practice SQL queries and Python coding challenges on Hackerrank & LeetCode. Strengthening your problem-solving skills will prepare you for interviews.

Data Analytics Courses: t.me/dataanalysisresourcestp/69

Best Data Analytics Resources: topmate.io/learning_resources/1456762/

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🍻 Learn Computer Science from Harvard, Stanford, IBM, Microsoft, Google 🍻

❯ JavaScript
http://learn.microsoft.com/training/paths/web-development-101/

https://t.me/javascriptresourcestp

❯ TypeScript
http://learn.microsoft.com/training/paths/build-javascript-applications-typescript/

❯ Mathematics (incl. Statistics)
ocw.mit.edu/search/?d=Mathematics&s=department_course_numbers.sort_coursenum

❯ Data Science
cognitiveclass.ai/courses/data-science-101

https://t.me/datascienceresourcestp

❯ C#
http://learn.microsoft.com/users/dotnet/collections/yz26f8y64n7k07

Microsoft Free Courses: https://t.me/freecoursescentre/159

More Resources Here
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💻 Monday Reminder for Beginner Devs

If you didn’t start last week, start today.

If you struggled last week, this week will be better.

If you started last week and continued today, you’re building consistency.

Keep showing up.
Do it for 4 weeks straight, and you’ll start to feel the shift.
But don’t slow down then make sure to keep the monumentum. Speed up. Keep going. That’s how progress compounds.

🔆 t.me/techpsyche

Meta releases its first frontier model, Muse Wonder

Meta's Superintelligence Lab has launched its first frontier AI models, Muse Wonder and Muse Wonder Full. Larger and more capable than the previous lightweight Muse Spark, these new models perform strongly on complex tasks like coding and rival competitors like Fable 5.1 and GPT-6 Astra.

A standout feature is "active memory," allowing the models to retain and synthesize user information over extended periods, scoring highest on the MemoryBench framework.

Trained at Meta's Prometheus data center in Ohio, the standard Wonder model is available via the Meta Model API at $4 per million input tokens and $20 per million output tokens. Meanwhile, the advanced Wonder Full variant is restricted exclusively to Muse Code subscribers and will power the ongoing Muse agent ecosystem.

🔆 t.me/techpsyche

Make no Mistakes

Complete Roadmap to learn Generative AI in 2 months 👇👇

Weeks 1-2: Foundations
1. Learn Basics of Python: If not familiar, grasp the fundamentals of Python, a widely used language in AI.
2. Understand Linear Algebra and Calculus: Brush up on basic linear algebra and calculus as they form the foundation of machine learning.

Weeks 3-4: Machine Learning Basics
1. Study Machine Learning Fundamentals: Understand concepts like supervised learning, unsupervised learning, and evaluation metrics.
2. Get Familiar with TensorFlow or PyTorch: Choose one deep learning framework and learn its basics.

Weeks 5-6: Deep Learning
1. Neural Networks: Dive into neural networks, understanding architectures, activation functions, and training processes.
2. CNNs and RNNs: Learn Convolutional Neural Networks (CNNs) for image data and Recurrent Neural Networks (RNNs) for sequential data.

Weeks 7-8: Generative Models
1. Understand Generative Models: Study the theory behind generative models, focusing on GANs (Generative Adversarial Networks) and VAEs (Variational Autoencoders).
2. Hands-On Projects: Implement small generative projects to solidify your understanding. Experimenting with generative models will give you a deeper understanding of how they work. You can use platforms such as Google's Colab or Kaggle to experiment with different types of generative models.

Additional Tips:
- Read Research Papers: Explore seminal papers on GANs and VAEs to gain a deeper insight into their workings.
- Community Engagement: Join AI communities on platforms like Reddit or Stack Overflow to ask questions and learn from others.

Pro Tip: Roadmap won't help unless you start working on it consistently. Start working on projects as early as possible.

2 months are good as a starting point to get grasp the basics of Generative AI but mastering it is very difficult as AI keeps evolving every day.

Best Resources to learn Generative AI 👇👇

Google Cloud Generative AI Path (https://www.cloudskillsboost.google/paths/118)

AI,Data Science & ML Resources: https://topmate.io/learning_resources/1406977

AI, ML & Deep Learning (httpst.me/airesourcestp/24)

NVIDIA AI & LLM Courses: https://intercomuniversity.com/free-courses/artificial-intelligence/nvidia-is-offering-6-ai-llm-courses-for-free/

Learn Python for Free (https://t.me/pythonresourcestp/22)

AI Cheat Sheet: https://t.me/airesourcestp/15

Prompt Engineering Course (https://www.deeplearning.ai/short-courses/chatgpt-prompt-engineering-for-developers/)

Prompt Engineering Guide (https://www.promptingguide.ai/)

Data Science Course (https://365datascience.pxf.io/Z6KDgk)

Machine Learning with Python Free Course (https://www.freecodecamp.org/learn/machine-learning-with-python/)

Machine Learning Free Book (https://t.me/mlresourcestp/16)

Resources WhatsApp channel (https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R)

Hands-on Machine Learning (https://t.me/mlresourcestp/19)

Deep Learning Nanodegree Program with Real-world Projects (https://www.udacity.com/course/deep-learning-nanodegree--nd101)

Like this post for more roadmaps ❤️

ENJOY LEARNING👍👍

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