Kaşif @SyntaxStrider

Data Analyst Bootcamp (FREE 35+ Hour Full Course) - SQL, Excel, Power BI, Python, AI & GitHub This 35-hour video is what I wish I'd had when I got started; it's for those with no degree or experience, helping one go from zero to job-ready. For this bootcamp, we’re focusing on the top 4 demanded skills for a Data Analyst 1️⃣ SQL (45% of job postings) 2️⃣ Excel (32%) 3️⃣ Python (31%) 4️⃣ Power BI (28%) But here's what makes this more than just a "How-To" video. It's not about the tools. The real work is learning how to be a data analyst and actually perform the analytics. The tools? They're just a necessity to facilitate it. And the best way to learn all that? You build it: 🛠 6 hands-on portfolio projects (because employers want experience) 🤖 AI built into your workflow to learn and work efficiently 🐙 GitHub to share everything you build So you finish each skill with something real to show, not just a "completed" badge. Now the real talk. I pulled the numbers from my own course-takers on how long each skill will take to learn: 🐘 SQL ~3 months ❎ Excel ~3 months 📊 Power BI ~2 months 🐍 Python ~6 months Realistically, that's 8 to 12 months to transition if you're doing this part-time. Alright, let's get to building. 🤙 youtube.com/watch?v=MOzEvN…

So many cats followed her because they all wanted to be petted by her. 🥹🧡

No Cats No Life @NoCatsNoLife_m

a day ago

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🎯Best Platforms For AI Agents AI agents are transforming how businesses automate tasks, build intelligent workflows, and create autonomous systems. From no-code platforms to advanced multi-agent frameworks, these tools help developers and teams build smarter AI-powered applications faster and more efficiently. LangChain ➔ Leading General-Purpose Agent Framework With Memory, Tool Use, And Orchestration. AutoGPT ➔ Autonomous AI Agent That Runs Tasks Independently With Iterative Planning Engines AgentGPT ➔ Browser-Based Interface To Build Autonomous AI Agents Without Requiring Coding CrewAI ➔ Open Framework Designed For Role-Based Agents And Collaborative Team Workflows Microsoft AutoGen ➔ Framework That Enables Structured Communication Between Multiple AI Agents SmolAgents ➔ Open-Source Agent Framework Optimized For Experimentation And Learning MetaGPT ➔ Scalable Open-Source Agent Framework For Complex Multi-Agent Engineering SuperAGI ➔ Developer-First Autonomous Agent Framework That Is Free, Open-Source, And GitHub-Based N8n ➔ Free Automation Tool Extensible With AI Agents And Advanced Workflows Botpress ➔ Open-Source Conversational AI Platform With Built-In Agent Capabilities Rasa ➔ Understands User Input And Responds With Accurate, Context-Aware Answers Mastra ➔ Open-Source TypeScript Framework For Building AI Agents And Workflows. ❤️ Like 🔁 Retweet 🔖 Bookmark Follow @MeenakshiYACS for more such posts #AI #ArtificialIntelligence #GenerativeAI #CareerGrowth #Upskilling

🚀 ALL FREE CERTIFICATION RESOURCES Level up your skills for FREE 👇 ☁️ AWS drive.google.com/drive/mobile/f… 🔐 CISSP drive.google.com/drive/mobile/f… 🛡️ CISA drive.google.com/drive/mobile/f… 📊 CISM drive.google.com/drive/mobile/f… ⚡ CRISC drive.google.com/drive/mobile/f… 📈 Digital Marketing drive.google.com/drive/mobile/f… 📌 Save this for later 🔁 Retweet to help others 🎯 Follow me @Sia_TechAi for more free tech resources 🚀

Ulu Başbuğ Atatürk’e düşman olan herkese düşmanım.

🎯Best Platforms For AI Agents AI agents are transforming how businesses automate tasks, build intelligent workflows, and create autonomous systems. From no-code platforms to advanced multi-agent frameworks, these tools help developers and teams build smarter AI-powered applications faster and more efficiently. LangChain ➔ Leading General-Purpose Agent Framework With Memory, Tool Use, And Orchestration. AutoGPT ➔ Autonomous AI Agent That Runs Tasks Independently With Iterative Planning Engines AgentGPT ➔ Browser-Based Interface To Build Autonomous AI Agents Without Requiring Coding CrewAI ➔ Open Framework Designed For Role-Based Agents And Collaborative Team Workflows Microsoft AutoGen ➔ Framework That Enables Structured Communication Between Multiple AI Agents SmolAgents ➔ Open-Source Agent Framework Optimized For Experimentation And Learning MetaGPT ➔ Scalable Open-Source Agent Framework For Complex Multi-Agent Engineering SuperAGI ➔ Developer-First Autonomous Agent Framework That Is Free, Open-Source, And GitHub-Based N8n ➔ Free Automation Tool Extensible With AI Agents And Advanced Workflows Botpress ➔ Open-Source Conversational AI Platform With Built-In Agent Capabilities Rasa ➔ Understands User Input And Responds With Accurate, Context-Aware Answers Mastra ➔ Open-Source TypeScript Framework For Building AI Agents And Workflows. ❤️ Like 🔁 Retweet 🔖 Bookmark Follow👤 @sakhil_ai for more such posts

Day 3 of #60DaysOfDE SQL BASICS SELECT – Used to choose which columns you want to see. SELECT first_name, country FROM Customers; Returns only the first_name and country columns. WHERE – Filters rows based on a condition. SELECT * FROM Customers WHERE age > 25; Returns customers older than 25. DISTINCT – Removes duplicate values. SELECT DISTINCT country FROM Customers; Returns each country only once. GROUP BY – Groups similar rows together, often used with aggregate functions like COUNT(), SUM(), or AVG(). SELECT country, COUNT(*) FROM Customers GROUP BY country; Shows how many customers belong to each country. ORDER BY – Sorts the results. SELECT * FROM Customers ORDER BY age DESC; Displays customers from oldest to youngest. LIMIT – Restricts the number of rows returned. SELECT * FROM Customers LIMIT 3; Returns only the first 3 rows. A simple example combining multiple clauses: SELECT country, COUNT(*) AS total_customers FROM Customers WHERE age > 20 GROUP BY country ORDER BY total_customers DESC LIMIT 3; This finds the top 3 countries with the most customers over the age of 20.

Agent AI Developer Roadmap for 2026 🚀 Stage 1: Learn Python well (FastAPI, APIs, async programming) Stage 2: Understand how LLMs work (Prompts, tokens, context windows, embeddings) Stage 3: Build basic RAG systems (PDF chat, semantic search, vector databases) Stage 4: Learn tool calling (APIs, databases, web search, calculators) Stage 5: Build single-agent systems (Planning, memory, tool usage) Stage 6: Build multi-agent workflows (Supervisor agent + specialized agents) Stage 7: Learn LangGraph / agent orchestration (State, routing, workflows, checkpoints) Stage 8: Evaluation & observability (Tracing, debugging, hallucination detection) Stage 9: Deployment & scaling (FastAPI, Docker, cloud, monitoring) Stage 10: Build real products (Customer support agents, research agents, coding agents, workflow automation) Most people stop at: "Hello World chatbot" Companies hire people who can build reliable AI systems.

Want to learn AI without spending thousands on courses? The companies building the future of AI are already teaching it for free. 10 free AI learning platforms worth bookmarking: 1. Anthropic anthropic.skilljar.com 2. Google grow.google/ai 3. Meta ai.meta.com/resources/ 4. NVIDIA developer.nvidia.com/cuda 5. Microsoft learn.microsoft.com/en-us/training/ 6. OpenAI academy.openai.com 7. IBM skillsbuild.org 8. AWS skillbuilder.aws 9. DeepLearning.AI deeplearning.ai 10. Hugging Face huggingface.co/learn Whether you're a student, developer, creator, or founder, these resources can help you build real AI skills. Comment "Learning" and I'll know this was useful. Bookmark this for later. Repost to help someone start their AI journey.

The AWS She Builds Mentorship Program returns for 2026! Get paired 1:1 with an AWS mentor for 12 weeks of career guidance & network expansion. Applications close June 30! Apply today 👉 go.aws/4uJDxcB

10 Completely FREE AI Courses for 2026: 1. Anthropic: anthropic.skilljar.com 2. Google: grow.google/ai 3. Meta: ai.meta.com/resources 4. NVIDIA: developer.nvidia.com/training 5. Microsoft: learn.microsoft.com/training 6. OpenAI: academy.openai.com 7. IBM: skillsbuild.org 8. AWS: skillbuilder.aws 9. DeepLearningAI: deeplearning.ai 10. Hugging Face: huggingface.co/learn

Types of APIs Every Developer Should Know 🚀 1. REST API Most common for web applications 2. GraphQL API Clients request exactly the data they need 3. WebSocket API Real-time communication (chat, gaming, trading) 4. gRPC API High-performance service-to-service communication 5. SOAP API Still used in many enterprise systems 6. Payment APIs Stripe, Razorpay, PayPal 7. Authentication APIs OAuth, JWT, SSO 8. Storage APIs AWS S3, Google Cloud Storage 9. AI APIs OpenAI, Anthropic, Gemini 10. Third-Party APIs Maps, Weather, Email, SMS, Social Media Most developers know how to consume APIs. The next level is learning how to design them.

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WE’RE HIRING — QA TESTER (REMOTE) Jobara is looking for a detail-oriented QA Tester to help ensure the quality, reliability, and performance of our platform before and after launch. Salary: ₦300,000 – ₦500,000 Experience: 2–4 Years Location: Fully Remote Requirements: •

1. The QA Automation Trap You're a manual QA tester. AI agents now write, execute, self-heal, and analyze test scripts across thousands of environments in seconds. Your manual clicking isn't a bottleneck companies pay for anymore. Pivot to AI Model Auditing. Stop testing basic UI workflows. Start testing LLM hallucination rates, edge cases, security vulnerabilities. Become the firewall between rogue AI output and the customer. You move from commoditized task to high-value security role. Companies are terrified of AI models leaking data or giving bad advice.

I see no difference

okay devs , what kind of work life would you actually choose? 🏢 Onsite or 🏠 Remote

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Important Sklearn Methods For Machine Learning