Denis Panjuta’s Post

Working of AI in a Nutshell Structural Breakdown - Step 1 : Problem Identification - Step 2 : Data Collection - Step 3 : Data Processing - Step 4 : Algorithm Selection - Step 5 : Model Training - Step 6 : Testing and Validation - Step 7 : Iteration and Improvement - Step 8 : Deployment - Step 9 : Feedback Loop - Step 10 : Continuous Learning Key Aspects of AI - Cognitive Computing - Computer Vision - Machine Learning - Neural Network - Deep Learning - Natural Language Processing [Explore more in the post] If you found this helpful don’t forget to save this for later and comment your thoughts. Join my newsletter or send me a DM "Newsletter” for more posts like this. Follow Denis Panjuta on Linkedin : https://lnkd.in/eUHjTBUi

20 Golden Rules To Write ChatGPT Prompts Here’s What’s Included : 1. Be Clear and Specific 2. Use Complete Sentences 3. Provide Context 4. Avoid Ambiguity 5. Include Examples 6. Use Proper Grammar & Spelling 7. Specify Desired Output 8. Define Technical Terms 9. Be Polite 10. Use Positive Language 11. Be Concise 12. Avoid Asking Multiple Questions 13. Test and Refine 14. Provide Constraints 15. Be Open-Ended When Necessary 16. Indicate Form of Response 17. Ask for Step-by-Step Solutions 18. Use Logical Sequencing 19. Encourage Creativity 20. Include Necessary Details [Explore more in the post] If you found this helpful don’t forget to save this for later and comment your thoughts. Join my newsletter or send me a DM "Newsletter” for more posts like this. Follow Denis Panjuta on Linkedin : https://lnkd.in/eUHjTBUi

AI Tools Cheat Sheet Supertools - AI solutions like ChatGPT, Claude AI, and Perplexity AI offer unmatched capabilities. Customer Success - Improve interactions with tools like SecondNative and Dante for customized chatbots and sales coaching. Productivity - Boost efficiency with Tl;dv, Scheduler AI, AudioPen, Notion, and Goblin Tools. Design & Video - Enhance creativity with Midjourney, Leonardo AI, Runway, ElevenLabs, Opus, HeyGen, and Pebblely. Marketing - Optimize marketing with Opus, Ecomm Ads Pencil, Framer, and Pebblely. Copy & Content - Generate top-quality content using Hypotenuse AI, Surfer, Sybill, PaperPal, Lavender AI, and Humanatic AI. Sales - Boost sales with Sybill, Humanlinker, Humantic AI, and Maverick. Job Seekers - Improve job search with JobScan, RecLoss, and JobHunt. Resume Creation - Create standout resumes with Enhancv, Resume.io, and Kickresume. [Explore more in the post] If you found this helpful don’t forget to save this for later and comment your thoughts. Join my newsletter or send me a DM "Newsletter” for more posts like this. Follow Denis Panjuta on Linkedin : https://lnkd.in/eUHjTBUi

Massive List of Free Resources To Learn AI Youtube Channels : 1. 3Blue1Brown : https://lnkd.in/eS8pkr3E 2. CSDojo : https://lnkd.in/ewdS_Yxx 3. Analytics Vidhya : https://lnkd.in/ewqpajPt 4. Two Minutes Paper : https://lnkd.in/erxEFUhA 5. SentDex : https://lnkd.in/esJnehg5 6. Corey Schafer : https://lnkd.in/eftpqNpe 7. Alex The Analyst : https://lnkd.in/eNinHpkS Courses From Google : 1. Introduction to Generative AI : https://lnkd.in/ePUjRD2r 2. Prompt Design in Vertex AI : https://lnkd.in/eGyjTPmE 3. Introduction to Duet AI in Google Workspace : https://lnkd.in/e8rCyhQx 4. Responsible AI : https://lnkd.in/e9W6PMDs 5. Attention Mechanism : https://lnkd.in/e7BfySrq 6. Create Image Captioning Models : https://lnkd.in/e3ptPDqH 7. ML Pipelines : https://lnkd.in/ehWuBVEA Courses From IBM : 1. Introduction to Artificial Intelligence (AI) : https://lnkd.in/evKx9yUR 2. AI Workflow: ML, NLP : https://lnkd.in/gzJcRUkg 3. Applied AI with DeepLearning : https://lnkd.in/ghp3VQt 4. AI Workflow: AI in Production : https://lnkd.in/gy3gbt8e 5. The AI Ladder : https://lnkd.in/gmQ3eMYb 6. Building AI Applications : https://lnkd.in/gB2gNsVM 7. Machine Learning with Python : https://lnkd.in/dWX47JJ Courses From Linkedin : 1. Intro To AI : https://lnkd.in/gn-GMQjR 2. What is Generative AI : https://lnkd.in/dWWct5Z9 3. Generative AI : https://lnkd.in/dSQP69-Z 4. Generative AI For Creativity : https://lnkd.in/gS4K8J-d 5. Generative AI Ethics : https://lnkd.in/gbB9nid2 6. AI productivity Hack : https://lnkd.in/gzpdcQQR 7. Streamline Your Work : https://lnkd.in/gNkDxwTq Courses From Nvidia : 1. Accelerate Data Science Workflows : https://lnkd.in/gUnU3Yxn 2. Introduction to AI in the Data Center : https://lnkd.in/d3DdNxq9 3. Building Video AI Applications : https://lnkd.in/gkXmRBQW 4. Getting Started with AI on Jetson Nano : https://lnkd.in/gdKi6rn8 5. Building A Brain in 10 Minutes : https://lnkd.in/gsdbsTHA 6. Sensitive Information Detection with Morpheus : https://lnkd.in/gHtSUc4P 7. Generative AI Explained : https://lnkd.in/giU_S3gc Extras : 1. Simplilearn : https://lnkd.in/ewDyYZtF 2. Udemy : https://lnkd.in/eCYrbGph 3. MyGreatLearning : https://lnkd.in/eTQn7CqY 4. Deep Learning : https://lnkd.in/e943mtQJ Join my newsletter or send me a DM "Newsletter” for more posts like this. Follow Denis Panjuta on Linkedin : https://lnkd.in/eUHjTBUi

Data Scientist Roadmap 1. Mathematics & Statistics: Develop a solid understanding of probability theory, hypothesis testing, linear algebra (vectors, matrices), inferential statistics, descriptive statistics, and calculus. These concepts are fundamental for data analysis and machine learning algorithms. 2. Python: Gain proficiency in Python, including functions, data types, control structures, Pandas, Numpy, Scikit-Learn, syntax, data visualization, Matplotlib, Plotly, TensorFlow, PyTorch, data analysis, and Seaborn. Python is the backbone of data science programming. 3. SQL: Master SQL basics such as SELECT, INSERT, UPDATE, DELETE, as well as joins, subqueries, window functions, data optimization, database management, query optimization, and stored procedures. These skills are essential for working with large datasets. 4. Data Wrangling: Learn to handle missing values, data transformation, data normalization, and data cleaning efficiently. These tasks are key in preparing data for analysis. 5. Data Visualization: Use tools like Bokey, Plotly, Seaborn, Taipy, Matplotlib, PowerBI, Looker, and Tableau to create compelling visualizations that communicate insights effectively. 6. Machine Learning: Dive into supervised learning, unsupervised learning, linear regression, logistic regression, decision trees, K-Means clustering, hierarchical clustering, model evaluation, cross-validation, and ROC curve. Mastering these techniques is critical for building robust models. 7. Soft Skills: Enhance your problem-solving skills, critical thinking, communication skills, collaboration and teamwork, storytelling with data, presentation skills, and adaptability. These soft skills are vital for collaborating with teams and stakeholders effectively. [Explore more in the post] If you found this helpful don’t forget to save this for later and comment your thoughts. Join my newsletter or send me a DM "Newsletter” for more posts like this. Follow Denis Panjuta on Linkedin : https://lnkd.in/eUHjTBUi

Careers In AI Data Scientist - Core Skills: Python, R, Machine Learning, Data Visualization, Big Data technologies - Responsibilities: Develop models, mine and analyze data, translate business issues into data projects, communicate findings Data Analyst - Core Skills: SQL, Python, Data Wrangling, Statistical Analysis, Data Visualization tools - Responsibilities: Interpret data, create reports, identify trends, support decision-making AI Engineer - Core Skills: Programming, AI Frameworks, Robotics, NLP, Computer Vision - Responsibilities: Design AI models, develop systems, collaborate on improvements, integrate  AI in business Machine Learning Engineer - Core Skills: Python, Scala, Machine Learning Algorithms, Deep Learning Frameworks, Big Data tools - Responsibilities: Design ML applications, conduct experiments, implement algorithms, collaborate on deployment Data Engineer - Core Skills: Database Management, ETL Tools, Big Data technologies, Data Warehousing - Responsibilities: Build data architecture, develop processes, assemble datasets, ensure business alignment [Explore more in the post] If you found this helpful don’t forget to save this for later and comment your thoughts. Join my newsletter or send me a DM "Newsletter” for more posts like this. Follow Denis Panjuta on Linkedin : https://lnkd.in/eUHjTBUi

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Paid vs Free AI Tools 1. Productivity Tools: Discover the best AI tools for boosting your productivity, from project management and time tracking to office suites and online meetings. 2. Content Tools: Elevate your content creation process with AI-driven tools for paraphrasing, content writing, copywriting, and more. 3. Sales Tools: Enhance your sales strategy with AI-powered solutions designed to improve CRM, email management, and revenue growth. 4. Marketing Tools: Optimize your marketing efforts with AI tools for content optimization, video marketing, analytics, and social media management. [Explore more in the post] If you found this helpful don’t forget to save this for later and comment your thoughts. Join my newsletter or send me a DM "Newsletter” for more posts like this. Follow Denis Panjuta on Linkedin : https://lnkd.in/eUHjTBUi