DataSense

𝗪𝗲 𝗝𝘂𝘀𝘁 𝗟𝗮𝘂𝗻𝗰𝗵𝗲𝗱 - 𝗔𝗜 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 𝗠𝗮𝘀𝘁𝗲𝗿𝗰𝗹𝗮𝘀𝘀

Most people learn AI by building small demos. But 𝗿𝗲𝗮𝗹 𝗰𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝗱𝗼𝗻’𝘁 𝘀𝗵𝗶𝗽 𝗱𝗲𝗺𝗼𝘀… they ship production-grade AI systems.

Today we officially launched our new course where we teach how real AI software is designed, built, and deployed end-to-end — from idea → architecture → agents → production.

𝗛𝗲𝗿𝗲’𝘀 𝘄𝗵𝗮𝘁 𝘄𝗲 𝗰𝗼𝘃𝗲𝗿👇

🔹 How real AI applications are structured

🔹 Chatbot vs Agent vs Workflow vs Multi-Agent systems

🔹 How LLM + Tools actually work internally

🔹 Tool calling, runtime execution & API architecture

🔹 Memory, Knowledge, Action & Computation tools

🔹 FastAPI layer for exposing AI systems

🔹 CI/CD → Docker → Containers → Kubernetes flow

🔹 Scaling, Load Balancing & Self-Healing systems

🔹 How companies move from prototype → production

🔹 Real architecture thinking for production AI

This course is for AI Engineers, Developers, and Architects who want to move beyond demos and understand how real AI systems are built in industry.

If you want to build production-grade AI, not just notebooks, this is for you.

👉 𝗘𝗻𝗿𝗼𝗹𝗹 𝗵𝗲𝗿𝗲: topmate.io/datasense/page/nGXIdGuoyDmNJ2m9u0

#AI #GenAI #AIEngineering #SoftwareArchitecture #Agents #LLM #SystemDesign #MLOps #Kubernetes #DataSense

4 days ago | [YT] | 0

DataSense

𝗠𝗼𝘀𝘁 𝗥𝗔𝗚 𝘁𝘂𝘁𝗼𝗿𝗶𝗮𝗹𝘀 𝘄𝗼𝗿𝗸 𝗶𝗻 𝗱𝗲𝗺𝗼𝘀 𝗮𝗻𝗱 𝗯𝗿𝗲𝗮𝗸 𝗶𝗻 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻.

This workshop is about understanding why that happens and how to fix it.

𝗜𝗻 𝘁𝗵𝗶𝘀 𝗳𝗿𝗲𝗲 𝗹𝗶𝘃𝗲 𝘀𝗲𝘀𝘀𝗶𝗼𝗻, 𝘄𝗲’𝗹𝗹 𝗯𝘂𝗶𝗹𝗱 𝘆𝗼𝘂𝗿 𝗳𝗶𝗿𝘀𝘁 𝗥𝗔𝗚 𝗽𝗿𝗼𝗷𝗲𝗰𝘁 𝗲𝗻𝗱-𝘁𝗼-𝗲𝗻𝗱, then deliberately break it to understand:

1.⁠ ⁠Why toy RAG systems fail in real-world usage

2.⁠ ⁠⁠The core layers of production-grade RAG architecture

3.⁠ ⁠⁠Common issues teams face after deployment (latency, bad retrieval, cost, drift)

4.⁠ ⁠⁠What matters beyond chunking & embeddings

5.⁠ ⁠⁠How these issues are actually handled in production systems

This is not a copy-paste tutorial.

You’ll build a working RAG app first, see its limitations, and then learn how those problems are addressed in real production-grade applications.


📅 Sunday, 8 Feb | 8 AM IST

🎯 Free • Live • Limited spots



👉 𝗘𝗻𝗿𝗼𝗹𝗹 𝗵𝗲𝗿𝗲: topmate.io/datasense/page/LXPdG322V3zusdumql

4 days ago | [YT] | 0

DataSense

𝗦𝗤𝗟 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗪𝗼𝗿𝗸𝘀𝗵𝗼𝗽 #𝟮: 𝗦𝗻𝗮𝗽𝗰𝗵𝗮𝘁 𝗦𝘁𝗿𝗲𝗮𝗸 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀

Ever wondered how apps like Snapchat keep users coming back every single day?

In this hands-on workshop, we’ll reverse-engineer the streak & retention logic using advanced SQL Window Functions and build real product-level analytics.

📅 𝗦𝘂𝗻𝗱𝗮𝘆, 𝗙𝗲𝗯 𝟭 | ⏰ 𝟵 𝗔𝗠 𝗜𝗦𝗧

𝗪𝗵𝗮𝘁 𝘆𝗼𝘂’𝗹𝗹 𝗹𝗲𝗮𝗿𝗻:

• Track user streaks and activity gaps

• Predict churn using LAG/LEAD & rolling windows

• Segment users by engagement consistency

• Write interview-ready window function queries

This is not theory. You’ll build a complete retention analytics project that you can showcase in interviews.

👉 𝗥𝗲𝗴𝗶𝘀𝘁𝗲𝗿 𝗵𝗲𝗿𝗲: topmate.io/datasense/1921480

1 week ago | [YT] | 0

DataSense

𝗝𝘂𝘀𝘁 𝗟𝗮𝘂𝗻𝗰𝗵𝗲𝗱: 𝗚𝗲𝗻 𝗔𝗜 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝟱 - 𝗔𝗴𝗲𝗻𝘁-𝗗𝗿𝗶𝘃𝗲𝗻 𝗗𝗮𝘁𝗮 𝗠𝗶𝗴𝗿𝗮𝘁𝗶𝗼𝗻

We’ve just released Gen AI Project 5, a hands-on, 𝟯-𝗵𝗼𝘂𝗿 𝗽𝗿𝗼𝗷𝗲𝗰𝘁 𝘄𝗵𝗲𝗿𝗲 𝘆𝗼𝘂 𝗯𝘂𝗶𝗹𝗱 𝗮 𝗿𝗲𝗮𝗹 𝗔𝗜-𝗮𝗴𝗲𝗻𝘁 𝗽𝗼𝘄𝗲𝗿𝗲𝗱 𝗘𝗧𝗟 𝘀𝘆𝘀𝘁𝗲𝗺 𝘁𝗵𝗮𝘁 𝗺𝗶𝗴𝗿𝗮𝘁𝗲𝘀 𝗱𝗮𝘁𝗮 𝗳𝗿𝗼𝗺 𝗦𝗻𝗼𝘄𝗳𝗹𝗮𝗸𝗲 → 𝗚𝗼𝗼𝗴𝗹𝗲 𝗖𝗹𝗼𝘂𝗱 using:

🤖 LLM Agents
⚙️ LangChain + FastAPI
🧭 Agent Orchestration
📊 Cloud-grade ETL Design
💬 Chat-based Control Panel
🔁 Automated Sync & Versioning

This is how modern data platforms are moving:
From static pipelines ➜ to autonomous, reasoning agents.

𝗣𝗲𝗿𝗳𝗲𝗰𝘁 𝗳𝗼𝗿:
Data Engineers • AI Engineers • Cloud Architects • GenAI Builders

𝗢𝘂𝘁𝗰𝗼𝗺𝗲:
You’ll walk away with a production-style Agentic ETL Platform and a strong portfolio project.

👉 𝗘𝗻𝗿𝗼𝗹𝗹 𝗵𝗲𝗿𝗲: lnkd.in/gwawsXzH

hashtag#GenAI hashtag#DataEngineering hashtag#AIProjects hashtag#AgenticAI hashtag#ETL hashtag#LangChain hashtag#FastAPI hashtag#Snowflake hashtag#GoogleCloud hashtag#DataSense

2 weeks ago | [YT] | 1

DataSense

𝗚𝗲𝗻𝗔𝗜 𝗶𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄𝘀 𝗮𝗿𝗲𝗻’𝘁 𝗮𝗯𝗼𝘂𝘁 𝗺𝗲𝗺𝗼𝗿𝗶𝘇𝗶𝗻𝗴 𝘁𝗼𝗼𝗹𝘀 𝗼𝗿 𝗯𝘂𝘇𝘇𝘄𝗼𝗿𝗱𝘀.


They test how you think, design, and explain real GenAI systems.


In this workshop, we focus only on what interviewers actually evaluate.


𝗪𝗵𝗮𝘁 𝘄𝗲’𝗹𝗹 𝗰𝗼𝘃𝗲𝗿:

1.⁠ ⁠Do you really need Machine Learning before GenAI (and when you don’t)

2.⁠ ⁠⁠What GenAI interview questions actually look like

3.⁠ ⁠⁠How interviewers expect you to explain agents

4.⁠ ⁠⁠What RAG optimization really means in interviews


No theory overload. No hype. Just interview-relevant clarity.


👉 𝗥𝗲𝗴𝗶𝘀𝘁𝗲𝗿 𝗵𝗲𝗿𝗲: lnkd.in/g26j7axZ

1 month ago | [YT] | 2

DataSense

𝗚𝗲𝗻𝗔𝗜 𝗶𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄𝘀 𝗼𝗳𝘁𝗲𝗻 𝗳𝗼𝗰𝘂𝘀 𝗼𝗻 𝗵𝗼𝘄 𝘆𝗼𝘂 𝗲𝘅𝗽𝗹𝗮𝗶𝗻 𝘀𝘆𝘀𝘁𝗲𝗺 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀, 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝘄𝗵𝗮𝘁 𝘁𝗼𝗼𝗹𝘀 𝘆𝗼𝘂’𝘃𝗲 𝘂𝘀𝗲𝗱.

I’m hosting a session on How to Crack GenAI Interviews, covering how interviewers typically evaluate:

• RAG and system design questions
• agent and tool-based workflows
• trade-offs around cost, latency, and reliability

It’s practical and interview-focused.

𝗕𝗼𝗼𝗸 𝗵𝗲𝗿𝗲: lnkd.in/gqkxKnF5

hashtag#GenAI hashtag#AIInterviews hashtag#LLM hashtag#RAG hashtag#GenAIEngineer

1 month ago | [YT] | 1

DataSense

𝗠𝗼𝘀𝘁 𝗽𝗲𝗼𝗽𝗹𝗲 𝗸𝗲𝗲𝗽 𝘄𝗮𝘁𝗰𝗵𝗶𝗻𝗴 𝘁𝘂𝘁𝗼𝗿𝗶𝗮𝗹𝘀, 𝘄𝗮𝗶𝘁𝗶𝗻𝗴 𝗳𝗼𝗿 𝘁𝗵𝗲 “𝗿𝗶𝗴𝗵𝘁 𝘁𝗶𝗺𝗲” 𝘁𝗼 𝘀𝘁𝗮𝗿𝘁 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴. 𝗧𝗿𝘂𝘁𝗵 𝗶𝘀 - 𝘁𝗵𝗮𝘁 𝗺𝗼𝗺𝗲𝗻𝘁 𝗻𝗲𝘃𝗲𝗿 𝗰𝗼𝗺𝗲𝘀.


So here’s your chance to build something real.

𝗝𝗼𝗶𝗻 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗶𝗻 𝟭𝟴𝟬 – 𝗧𝗵𝗲 𝗚𝗲𝗻𝗔𝗜 𝗕𝘂𝗶𝗹𝗱 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲, 𝗮 𝟯-𝗵𝗼𝘂𝗿 𝗵𝗮𝗻𝗱𝘀-𝗼𝗻 𝘀𝗽𝗿𝗶𝗻𝘁 where you’ll get a real-world problem statement, build a working GenAI project in 2 hours, and spend the last hour reviewing and improving your solution together.


Limited seats. Enrollments are open.

👉 topmate.io/datasense/1807073

2 months ago | [YT] | 3

DataSense

❌ 𝗗𝗼𝗻’𝘁 𝗦𝗸𝗶𝗽 ❌

𝗪𝗵𝘆 𝗠𝗼𝘀𝘁 𝗣𝗲𝗼𝗽𝗹𝗲 𝗘𝗻𝗿𝗼𝗹𝗹 𝗶𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗯𝘂𝘁 𝗡𝗲𝘃𝗲𝗿 𝗙𝗶𝗻𝗶𝘀𝗵?

We’ve all been there.

That rush of excitement when you click “𝗘𝗻𝗿𝗼𝗹𝗹.” You imagine the new skill, the certificate on your LinkedIn, maybe even the career change. For a moment, it feels like your life just took a leap forward.

𝗕𝘂𝘁 𝘁𝗵𝗲𝗻… 𝗿𝗲𝗮𝗹𝗶𝘁𝘆.

The first week goes fine. The second week, you’re “busy.” By the third week, you tell yourself you’ll “catch up later.” And by the fourth week, you’ve quietly stopped opening the course altogether.

𝗪𝗵𝘆 𝗱𝗼𝗲𝘀 𝘁𝗵𝗶𝘀 𝗵𝗮𝗽𝗽𝗲𝗻 𝘁𝗼 𝘀𝗼 𝗺𝗮𝗻𝘆 𝗼𝗳 𝘂𝘀?

Because motivation is temporary. The energy you feel on Day 1 is like a sugar rush - it spikes, then crashes. What actually carries you through is discipline, clarity, and accountability.

Most people don’t finish because:


1.⁠ ⁠They take on too many courses at once, believing more is better, but end up doing nothing properly.
2.⁠ ⁠⁠They don’t have a clear reason why they’re learning - so the moment it gets hard, they lose interest.
3.⁠ ⁠⁠They don’t have structure or accountability - no deadlines, no peers pushing them, no mentor checking in.
4.⁠ ⁠⁠They get distracted by the next shiny topic, leaving half-finished lessons in the dust.

The truth is, courses don’t fail people. People fail courses.

𝗦𝗼 𝘄𝗵𝗮𝘁’𝘀 𝘁𝗵𝗲 𝗳𝗶𝘅?

Don’t chase 10 courses. Pick one. Define exactly why you’re doing it maybe to build a project, maybe to crack an interview.

Make small progress every single day, even if it’s 20 minutes. And surround yourself with a group or mentor who won’t let you quietly quit.

Finishing a course is not about collecting certificates. It’s about building a habit of seeing things through. And that habit compounds into real skills - the kind that actually change careers, businesses, and lives.

𝗦𝗼, 𝗮𝘀𝗸 𝘆𝗼𝘂𝗿𝘀𝗲𝗹𝗳 𝗵𝗼𝗻𝗲𝘀𝘁𝗹𝘆:

👉 How many courses have you started but left unfinished?

👉 And what would happen if, this time, you finally saw it through?

4 months ago | [YT] | 3

DataSense

𝗪𝗮𝘁𝗰𝗵 𝗧𝗵𝗲𝘀𝗲 𝗙𝗿𝗲𝗲 𝗩𝗶𝗱𝗲𝗼𝘀 𝗯𝘆 𝗗𝗮𝘁𝗮𝗦𝗲𝗻𝘀𝗲 𝘁𝗼 𝗜𝗻𝘀𝘁𝗮𝗻𝘁𝗹𝘆 𝗨𝗽𝘀𝗸𝗶𝗹𝗹

Curated for developers, product minds & AI learners.

𝟭. 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗮𝗻 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁? 𝗕𝘂𝗶𝗹𝗱 𝗼𝗻𝗲 𝘂𝘀𝗶𝗻𝗴 𝘁𝗵𝗲 𝗥𝗘𝗔𝗖𝗧 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸

lnkd.in/gx5xWZeD

𝟮. 𝗥𝗔𝗚 𝗖𝗵𝗮𝘁𝗯𝗼𝘁 𝗧𝘂𝘁𝗼𝗿𝗶𝗮𝗹 – 𝗟𝗲𝗮𝗿𝗻 𝗵𝗼𝘄 𝗥𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹-𝗔𝘂𝗴𝗺𝗲𝗻𝘁𝗲𝗱 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻 𝘄𝗼𝗿𝗸𝘀

lnkd.in/gifFCcQq

𝟯. 𝗡𝗮𝘁𝘂𝗿𝗮𝗹 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝘁𝗼 𝗦𝗤𝗟 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 – 𝗖𝗼𝗻𝘃𝗲𝗿𝘁 𝘂𝘀𝗲𝗿 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀 𝗶𝗻𝘁𝗼 𝗾𝘂𝗲𝗿𝗶𝗲𝘀

lnkd.in/gMaq4WQ2

𝟰. 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗟𝗮𝗻𝗴𝗴𝗿𝗮𝗽𝗵- 𝗘𝗻𝗱 𝘁𝗼 𝗘𝗻𝗱 𝗣𝗿𝗼𝗷𝗲𝗰𝘁

lnkd.in/gFhHwWbd

𝟱. 𝗚𝗶𝘁𝗛𝘂𝗯 𝗔𝗰𝘁𝗶𝗼𝗻𝘀 𝗖𝗿𝗮𝘀𝗵 𝗖𝗼𝘂𝗿𝘀𝗲 – 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀 𝗹𝗶𝗸𝗲 𝗮 𝗽𝗿𝗼

lnkd.in/g9G8Pfdw

𝟲. 𝗥𝗔𝗚 𝗶𝗻 𝗡𝟴𝗡 (𝗡𝗼 𝗖𝗼𝗱𝗲) – 𝗕𝘂𝗶𝗹𝗱 𝘀𝗺𝗮𝗿𝘁 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀 𝘄𝗶𝘁𝗵𝗼𝘂𝘁 𝘄𝗿𝗶𝘁𝗶𝗻𝗴 𝗰𝗼𝗱𝗲

lnkd.in/gKrdS9gK

𝟳. 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗧𝗼𝗼𝗹 𝗖𝗮𝗹𝗹𝗶𝗻𝗴? – 𝗣𝗹𝘂𝗴 𝗿𝗲𝗮𝗹-𝘄𝗼𝗿𝗹𝗱 𝘁𝗼𝗼𝗹𝘀 𝗶𝗻𝘁𝗼 𝗔𝗜

lnkd.in/g987iFkF

𝟴. 𝗛𝗼𝘄 𝘁𝗼 𝗦𝗰𝗮𝗹𝗲 𝗮𝗻 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 – 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁 𝗳𝗼𝗿 𝟭 𝘂𝘀𝗲𝗿 𝗼𝗿 𝟭 𝗺𝗶𝗹𝗹𝗶𝗼𝗻

lnkd.in/gF_c4w8Z

𝟵. 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗗𝗼𝗰𝗸𝗲𝗿? 𝗕𝘂𝗶𝗹𝗱 𝗬𝗼𝘂𝗿 𝗙𝗶𝗿𝘀𝘁 𝗗𝗼𝗰𝗸𝗲𝗿 𝗜𝗺𝗮𝗴𝗲

lnkd.in/g2awvdeC

8 months ago | [YT] | 4

DataSense

🚀 𝗟𝗮𝘂𝗻𝗰𝗵𝗶𝗻𝗴 𝗮 𝗛𝗮𝗻𝗱𝘀-𝗢𝗻 𝗪𝗼𝗿𝗸𝘀𝗵𝗼𝗽: 𝗕𝘂𝗶𝗹𝗱 𝗬𝗼𝘂𝗿 𝗢𝘄𝗻 𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗔𝗜 𝗖𝗵𝗮𝘁𝗯𝗼𝘁 𝘄𝗶𝘁𝗵 𝗦𝗺𝗮𝗿𝘁 𝗖𝗮𝗰𝗵𝗶𝗻𝗴!


LLMs are powerful—but they’re 𝘀𝗹𝗼𝘄 𝗮𝗻𝗱 𝗲𝘅𝗽𝗲𝗻𝘀𝗶𝘃𝗲 when every query hits the model.

Let’s change that.

In this 2-day weekend workshop, you’ll build a production-ready chatbot that:

✅ Answers user queries via LLM

✅ Caches similar questions using semantic similarity (FAISS/Pinecone)

✅ Avoids redundant LLM calls

✅ Is deployed using FastAPI, Docker, and GitHub Actions


💡 Whether you’re building internal Q&A systems, customer support bots, or knowledge assistants—this is built for you.

🎯 𝗥𝗲𝗴𝗶𝘀𝘁𝗲𝗿 𝗻𝗼𝘄: topmate.io/datasense/1479867

🎁𝗙𝗶𝗿𝘀𝘁 𝟭𝟬 𝘂𝘀𝗲𝗿𝘀 𝗴𝗲𝘁 𝟮𝟬% 𝗢𝗙𝗙 𝘄𝗶𝘁𝗵 𝗰𝗼𝗱𝗲 𝗖𝗔𝗖𝗛𝗘

#AI #Chatbots #LLM #FastAPI #Docker #Langchain #SemanticCaching #VectorDB #EnterpriseAI #PythonWorkshop #GitHubActions #LLMApps

10 months ago | [YT] | 1