OpenAILearning | Notes, Course, & Resources

OpenAILearning | Notes, Course, & Resources

2/13/2025, 3:57:56 AM

opy and paste these 𝗖𝗵𝗮𝘁𝗚𝗣𝗧  𝗣𝗿𝗼𝗺𝗽𝘁𝘀 to write a 𝗸𝗶𝗹𝗹𝗲𝗿 𝗥𝗲𝘀𝘂𝗺𝗲: Make ATS friendly RESUME that get around 90+ ATS score and higher chances of approval. 1. Act as a highly experienced resume writer and optimizer. Your goal is to write my resume for a [Profession] with [Number] years of experience. I'll provide the resume text, and you'll analyze it. 2. Resume Rules: Follow these '8 Simple Tips' to make my resume job-ready: 7-Second Rule, ATS Optimization, "Above the Fold", Quantifiable Impact, Skill Match, White Space, Storytelling, and Social Proof. Avoid buzzwords and clichés. 3. Summary Creation: Craft a compelling summary that captures my key skills and accomplishments as a [Profession]. Highlight key skills and technologies, quantify achievements, focus on results, align with employer needs, and avoid buzzwords. 4. Work Experience: Create a compelling Work Experience section that showcases my key skills, accomplishments, and contributions to previous employers. Tailor it to the specific job I'm targeting, highlighting relevant experience and quantifiable results. 5. Skills Section: Generate a Skills section, categorized into Technical Skills and Soft Skills, highlighting those most relevant to the target job description. Provide specific examples to demonstrate soft skills in action. 6. Projects Showcase: Identify any projects that can further enhance my resume and showcase my skills and experience. Focus on impact, relevance, and quantified achievements. 7. Education & Certification: Generate an Education & Certification section, listing degrees and certifications in reverse chronological order. Highlight relevant qualifications and certifications. 8. Final Resume Review: Perform a thorough final review of my resume to ensure it is polished, professional, and error-free. Check for typos, clarity, impact, ATS optimization, buzzwords, consistency, and overall flow. I have created in-depth version of these prompts that can actually generate high ATS targeted resume that has higher chances of approval. . . . Get access to the premium version of these 10 FOLLOW UP prompts that you can keep asking to ChatGPT or Gemini Pro to create a personalized resume. => https://beginnersblog1.gumroad.com/l/ChatGPT-Prompts-Generate-High-ATS-Recruiter-Friendly-Targeted-Resume-to-Land-Your-Dream-Job/ . Use Coupon code: beginner50

OpenAILearning | Notes, Course, & Resources

2/13/2025, 3:26:39 PM

https://www.linkedin.com/posts/beginners-blog_its-easy-to-forget-how-rapidly-technology-activity-7295825209176035328-uInn

OpenAILearning | Notes, Course, & Resources

2/2/2025, 2:19:50 AM

8 Machine Learning Algorithms ( A quick revision) 👇 1. Linear Regression: Predicts numbers (e.g., house prices). Straight line fit. Easy, but sensitive to outliers. 2. Logistic Regression: Predicts categories (e.g., spam/not spam). Uses probabilities. Great for classification. 3. Decision Tree: Flowchart-like decisions. Easy to visualize. Prone to overfitting. 4. Random Forest: Multiple decision trees combined. More robust. Handles complex data. 5. SVM: Finds the best dividing line (or plane). Effective, but can be slow. Uncovering Patterns: 6. K-Means Clustering: Groups similar data. Great for finding hidden structures. Requires pre-defined clusters. 7. KNN: Classifies based on neighbors. Simple, but computationally intensive. Simplifying Complexity: 8. Dimensionality Reduction: Reduces features. Makes data easier to handle. Improves model efficiency. Real-World Examples (Super Quick Hits): - Linear/Logistic Regression: House prices, spam filters. - Decision Tree/Random Forest: Medical diagnoses, credit scores. - SVM: Image recognition, text sorting. - K-Means: Customer groups, anomaly detection. - KNN: Recommendations, image recognition. - Dimensionality Reduction: Image compression, feature extraction. . . . Best online courses to MASTER Machine Learning 👇👇👇👇 1️⃣ Machine Learning by Andrew Ng (Stanford University) https://imp.i384100.net/5gNjr9 2️⃣ Deep Learning Specialization by deeplearning.ai https://imp.i384100.net/21N1mM 3️⃣ Mathematics for Machine Learning Specialization by Imperial College London https://imp.i384100.net/OrxkQW 4️⃣ Applied Data Science with Python Specialization by University of Michigan https://imp.i384100.net/jrd33e 5️⃣ Advanced Machine Learning by Google Cloud https://imp.i384100.net/5gobn1 6️⃣ Machine Learning with Python by IBM https://imp.i384100.net/R57KmX 7️⃣ Supervised Machine Learning: Regression and Classification https://imp.i384100.net/g109vB 8️⃣ Unsupervised Learning, Recommenders, Reinforcement Learning by University of Alberta https://imp.i384100.net/NkL5k2 9️⃣ Practical Machine Learning by Johns Hopkins University https://imp.i384100.net/7aGMzY 🔟 How Google does Machine Learning by Google Cloud https://imp.i384100.net/xL2ZYx . . . Join NextCareerStep to master demanding IT skills in every week. Plus, Receive FREE resources like 👇 - Roadmaps - Cheatsheet - Checklist - Resume temples 5000 people already joined 👇 https://nextcareerstep.beehiiv.com/subscribe/ . . .