What is ByteByteAI – Learn by Doing. Become an AI Engineer for Cheap?
Learning AI Architecture: From Cursor Novice to Expert in 23 Thrilling Hours
Perhaps hoping you could develop smart AI solutions rather than just consuming them; have you ever found yourself confused by all the AI jargon whirling about internet forums? Welcome to the deep dive you never knew you needed as we use the esteemed program, AI Architect – Cursor Mastery – Zero to Expert – 23 Hours of Practical Development, to untangle the art and science underlying AI architecture.
This is a rollicking, brain-teasing, skill-sharpening trip from novice to expert—all in just 23 hours of hands-on, practical learning—not just another AI course. This book provides all you need to know about conquering the AI architectural mountain, regardless of your age—35 and looking to change your profession or just an inquisitive mind ready to create the next killer app.
Let us buckle in and get going.
Why Architecture of AI Matters Right Now More Than Ever: Artificial intelligence is transforming our homes, offices, and even those casual conversations with our smart devices—not a passing trend. Rising at a CAGR of 37.3% between 2023 and 2030, Statista projects that the global AI industry will reach $1.81 trillion by 2030. There is a yawning void in this fast changing terrain for those who not only know what artificial intelligence does but also who can construct whole solutions from start and do so deftly.
AI Architect; Zero to Expert; Cursor Mastery; 23 Hours of Practical Development bridges that gap, demystifying AI architectures and showing you how to wield the cursor like a maestro, building, developing, and deploying actual AI systems.
The AI Architect: Zero to Expert Experience – Cursor Mastery Looks like a useful curriculum including practical problems.
This kind of course will not cause your brain to whirl in theoretical clouds. Rather, you will:
Start with zero: < Have not used Python or TensorFlow before? Not a concern.
Create, not merely observe. Attack real-world case studies ranging from recommendation engines to natural language understanding bots.
Become the master of the cursor. Discover the fundamental “cursor” idea for managing datasets, negotiating models, and debugging unanticipated neural network peculiarities.
23 Hours: Why Exactly This Number?
There is science to explain the craziness. Malcolm Gladwell famously popularized the “10,000-hour rule,” yet you really have a work, a life, and binge-worthy shows to watch. This all-in-one application thereby compiles years of scattered YouTube tutorials into a condensed 23-hour route plan. After all, the average adult’s ability for focused learning peaks after ninety minutes; dividing the road into bite-sized courses helps you recall more and reduces stress.
Important Chapters Unpacked
Let’s go through some of the highlights you will come across methodically.
Arriving to Base Camp: The Foundations
You will find yourself grounded here. Knowing the fundamental design of simple neural networks can help you to grasp:
From weights and biases to activation functions, what makes artificial intelligence “tick”?
The holy trio of algorithms, models, and data.
How the notorious cursor slices massive databases and provides bite-sized, processable bits for your models?
Rising Higher: Middle Knowledge
The actual adventure starts right now. You’ll pick up:
Like a professional, clean and prepare data utilizing clever cursor movements for speed.
Tune hyperparameters (that means modify your recipe to produce the ideal batch of artificial intelligence cookies).
Leverage pre-trained models with transfer learning—sort of as standing on the shoulders of AI behemoths.
Mastery of Apex: Overcoming Practical Problems
By hour twenty-three, you will be designing artificial intelligence rather than only “knowing” it. Projects culminating in a capstone include:
Forecasting complicated trends: (financial markets, consumer behavior, or even if your next plant will survive neglect.)
Natural language processing in action: running sentiment analysis and chatbots with power.
System of vision: Teaching your own systems of image classification.
Practical debugging, troubleshooting, and optimization advice permeates all of these projects to help you never feel lost.
Why Choose Zero to Expert – Cursor Mastery – AI Architect – 23 Hours of Practical Development Over Others?
Maths Never Lie
With practical education, completion rates soar. Students enrolled in project-based AI classes are 68% more likely to graduate according to Coursera.
Professionals learning AI architecture quadruple their average pay; Payscale notes U.S. salaries for advanced AI positions ranging from $102,000 to $ 170,000.
Customized for Real People
You are more than simply another visitor. Designed for adults (yes, even those over 35) with full lives, varied learning speeds, and varied experiences, the curriculum is You’ll find:
Bite-sized lessons and self-evaluations help with flexible pace.
Mentoring access: Q&A meetings with course designers.
Update lifetime: Remain current as artificial intelligence trends change.
The Cursor: Undressed Hero of AI Data Frameworks
Let’s have a store conversation. The “cursor” is the backbone for effective data input, preprocessing, and batching in both training and production situations, not only a weird sound in Python documentation.
How a Cursor Retieves Your Sanity
Consider dealing with a 10 million image dataset. Load everything all at once. Good fortune with regard to your memory and tolerance. Making use of a cursor implies:
Batches of data are how you handle it—perfect for constrained memory systems.
Debugging effectively is like seeing and manipulating data “midstream.” After an hour-long load process, there is no more battling cryptic mistakes.
Tips for Cursors You will learn
Apply real-time data augmentations (think of random cropping or color correction for image datasets) with cursors.
effective distributed training data sharding.
Smart checkpointing helps you never lose your position—even following a catastrophic laptop crash or power outage.
Student Success Stories: Emphasize actual outcomes.
Here’s evidence in the pudding if you’re wondering whether it’s feasible to move from zero to hero:
From HR manager to AI product manager, Jenna, 39 guided her team in creating an intelligent scheduler for remote employees. “The 23-hour focused structure made the impossible—possible.”
Nikolai, 42: Saved more than $1 million in first year expenses by using program abilities to maximize supply chain forecasts for a big retailer.
You’re not needed to be a math PhD or elusive code genius. You require curiosity, a readiness to learn, and the correct methodical approach.
Practical Development: All the Way to the Finish Line Beyond Theory
Theory is good until you run across a runtime issue that drives you to wish your laptop on fire. For this reason, AI Architect Cursor Mastery – Zero to Expert – 23 Hours of Practical Development stresses:
Tutorial troubleshooting: Find out what to check before you start to panic.
Notes on version control: Safe experimentation, simple rollbacks.
Practical demonstrations: hands-on guides From raw data to functional deployment, follow along with each step.
According to LinkedIn Learning data, exactly what you will discover here—85% of professionals prefer courses with direct application and project-based evaluation.
Your Competitive Edge—Your Zero to Expert Mindet
To be honest, companies want professionals not hobbyists. The disciplined road from zero to expert distinguishes you even if you learn everything on your own.
Skills you will carry with you:
planning scalable, modular artificial intelligence systems.
Effective data pipeline management helps to make the “big” datasets seem little.
Using the most recent artificial intelligence libraries, writing reusable, neat code.
And most essential, since change is the one constant in artificial intelligence, the assurance to keep learning.
FAQs: Everything You Want to Know (But Were Not Sure To Ask)
Does mastery of this call for a PhD?
Absolutely not! You are ready if you can utilize a spreadsheet and follow directions.
Is Python absolutely mandatory?
While every example employs Python, every idea is conveyed without reference to “assumed magic”. Python will seem more like an obedient puppy at the end than like a snake.
Will I be really an expert?
You will develop the knowledge required to create, troubleshoot, and implement workable artificial intelligence systems. And since technology is continually changing, you will also know where and how to keep studying.
In essence, your AI path begins here.
The world is changing. Businesses are rushing for talented AI architects able to close the gap between corporate value and academic theory.
You have every tool you need with AI Architect – Cursor Mastery – Zero to Expert – 23 Hours of Practical Development: a structured roadmap, hands-on projects, seasoned mentors, and a supporting community.
In less than a day’s worth of lessons, are you ready to transform from inquisitive observer into confident AI architect?
To register in AI Architect – Cursor Mastery – Zero to Expert – 23 Hours of Practical Development and transform your ambition into action now visit coursesfast.com. Already getting the spark? For further detailed advice, consult our Ultimate Guide to Creating Your First AI Application.
You now understand the feasible (and profitable) extent of artificial intelligence competence. Your initial step is the one lacking ingredient. The world—as well as your future AI discoveries—are waiting. Get right in.
Related update: ByteByteAI – Learn by Doing. Become an AI Engineer is featured in the May 2026 Courses On Budget premium course update, a monthly course drop covering new AI, business, marketing, ecommerce, design, real estate, self-development, and trading courses.
ByteByteAI Learn by Doing. Become an AI Engineer Index:
📂 Bonus – Visual Bundle
- 📂 Coding Interview Patterns
- 📄 001 Introduction to Two Pointers.html (812.99 KB)
- 📄 002 Pair Sum – Sorted.html (595.26 KB)
- 📄 003 Triplet Sum.html (941.63 KB)
- 📄 004 Is Palindrome Valid.html (638.79 KB)
- 📄 005 Largest Container.html (1.09 MB)
- 📄 006 Shift Zeros to the End.html (941.35 KB)
- 📄 007 Next Lexicographical Sequence.html (1.09 MB)
- 📄 008 Introduction to Hash Maps and Sets.html (480.19 KB)
- 📄 009 Pair Sum – Unsorted.html (682.54 KB)
- 📄 010 Verify Sudoku Board.html (928.04 KB)
- 📄 011 Zero Striping.html (2.11 MB)
- 📄 012 Longest Chain of Consecutive Numbers.html (591.74 KB)
- 📄 013 Geometric Sequence Triplets.html (1.68 MB)
- 📄 014 Introduction to Linked Lists.html (762.85 KB)
- 📄 015 Linked List Reversal.html (1.29 MB)
- 📄 016 Remove the Kth Last Node From a Linked List.html (661.68 KB)
- 📄 017 Linked List Intersection.html (736.14 KB)
- 📄 018 LRU Cache.html (2.22 MB)
- 📄 019 Palindromic Linked List.html (535.17 KB)
- 📄 020 Flatten a Multi-Level Linked List.html (1.45 MB)
- 📄 021 Introduction to Fast and Slow Pointers.html (303.97 KB)
- 📄 022 Linked List Loop.html (1017.31 KB)
- 📄 023 Linked List Midpoint.html (547.02 KB)
- 📄 024 Happy Number.html (510.25 KB)
- 📄 025 Introduction to Sliding Windows.html (903.22 KB)
- 📄 026 Substring Anagrams.html (1.02 MB)
- 📄 027 Longest Substring With Unique Characters.html (1.37 MB)
- 📄 028 Longest Uniform Substring After Replacements.html (2.31 MB)
- 📄 029 Introduction to Binary Search.html (1.00 MB)
- 📄 030 Find the Insertion Index.html (1.40 MB)
- 📄 031 First and Last Occurrences of a Number.html (1.54 MB)
- 📄 032 Cutting Wood.html (1.90 MB)
- 📄 033 Find the Target in a Rotated Sorted Array.html (1009.93 KB)
- 📄 034 Find the Median From Two Sorted Arrays.html (1.30 MB)
- 📄 035 Matrix Search.html (1.36 MB)
- 📄 036 Local Maxima in Array.html (1.44 MB)
- 📄 037 Weighted Random Selection.html (1.06 MB)
- 📄 038 Introduction to Stacks.html (583.28 KB)
- 📄 039 Valid Parenthesis Expression.html (656.32 KB)
- 📄 040 Next Largest Number to the Right.html (719.19 KB)
- 📄 041 Evaluate Expression.html (1.25 MB)
- 📄 042 Repeated Removal of Adjacent Duplicates.html (681.84 KB)
- 📄 043 Implement a Queue using Stacks.html (1.35 MB)
- 📄 044 Maximums of Sliding Window.html (1.84 MB)
- 📄 045 Introduction to Heaps.html (403.71 KB)
- 📄 046 K Most Frequent Strings.html (1.53 MB)
- 📄 047 Combine Sorted Linked Lists.html (732.91 KB)
- 📄 048 Median of an Integer Stream.html (826.06 KB)
- 📄 049 Sort a K-Sorted Array.html (1.82 MB)
- 📄 050 Introduction to Intervals.html (391.93 KB)
- 📄 051 Merge Overlapping Intervals.html (1.36 MB)
- 📄 052 Identify All Interval Overlaps.html (777.45 KB)
- 📄 053 Largest Overlap of Intervals.html (805.46 KB)
- 📄 054 Introduction to Prefix Sums.html (519.53 KB)
- 📄 055 Sum Between Range.html (637.60 KB)
- 📄 056 K-Sum Subarrays.html (1.08 MB)
- 📄 057 Product Array Without Current Element.html (1.52 MB)
- 📄 058 Introduction to Trees.html (882.69 KB)
- 📄 059 Invert Binary Tree.html (953.69 KB)
- 📄 060 Balanced Binary Tree Validation.html (596.59 KB)
- 📄 061 Rightmost Nodes of a Binary Tree.html (807.77 KB)
- 📄 062 Widest Binary Tree Level.html (548.19 KB)
- 📄 063 Binary Search Tree Validation.html (1.51 MB)
- 📄 064 Lowest Common Ancestor.html (776.63 KB)
- 📄 065 Build Binary Tree From Preorder and Inorder Traversals.html (869.62 KB)
- 📄 066 Maximum Sum of a Continuous Path in a Binary Tree.html (1.31 MB)
- 📄 067 Binary Tree Symmetry.html (514.90 KB)
- 📄 068 Binary Tree Columns.html (639.98 KB)
- 📄 069 Kth Smallest Number in a Binary Search Tree.html (393.56 KB)
- 📄 070 Serialize and Deserialize a Binary Tree.html (849.45 KB)
- 📄 071 Introduction to Tries.html (528.66 KB)
- 📄 072 Design a Trie.html (1.24 MB)
- 📄 073 Insert and Search Words with Wildcards.html (472.48 KB)
- 📄 074 Find All Words on a Board.html (1.66 MB)
- 📄 075 Introduction to Graphs.html (824.41 KB)
- 📄 076 Graph Deep Copy.html (747.59 KB)
- 📄 077 Count Islands.html (934.56 KB)
- 📄 078 Matrix Infection.html (1.62 MB)
- 📄 079 Bipartite Graph Validation.html (566.49 KB)
- 📄 080 Longest Increasing Path.html (693.72 KB)
- 📄 081 Shortest Transformation Sequence.html (1.35 MB)
- 📄 082 Merging Communities.html (1.03 MB)
- 📄 083 Prerequisites.html (913.11 KB)
- 📄 084 Shortest Path.html (1.83 MB)
- 📄 085 Connect the Dots.html (1.37 MB)
- 📄 086 Introduction to Backtracking.html (593.64 KB)
- 📄 087 Find All Permutations.html (853.58 KB)
- 📄 088 Find All Subsets.html (638.46 KB)
- 📄 089 N Queens.html (707.42 KB)
- 📄 090 Combinations of a Sum.html (955.20 KB)
- 📄 091 Phone Keypad Combinations.html (565.76 KB)
- 📄 092 Introduction to Dynamic Programming.html (424.76 KB)
- 📄 093 Climbing Stairs.html (844.61 KB)
- 📄 094 Minimum Coin Combination.html (1.03 MB)
- 📄 095 Matrix Pathways.html (675.69 KB)
- 📄 096 Neighborhood Burglary.html (654.38 KB)
- 📄 097 Longest Common Subsequence.html (1014.02 KB)
- 📄 098 Longest Palindrome in a String.html (724.54 KB)
- 📄 099 Maximum Subarray Sum.html (989.94 KB)
- 📄 100 01 Knapsack.html (1.10 MB)
- 📄 101 Largest Square in a Matrix.html (1.21 MB)
- 📄 102 Introduction to Greedy Algorithms.html (399.54 KB)
- 📄 103 Jump to the End.html (1.01 MB)
- 📄 104 Gas Stations.html (999.53 KB)
- 📄 105 Candies.html (976.70 KB)
- 📄 106 Introduction to Sort and Search.html (328.35 KB)
- 📄 107 Sort Linked List.html (1.15 MB)
- 📄 108 Sort Array.html (921.31 KB)
- 📄 109 Kth Largest Integer.html (1.26 MB)
- 📄 110 Dutch National Flag.html (1.05 MB)
- 📄 111 Introduction to Bit Manipulation.html (523.13 KB)
- 📄 112 Hamming Weights of Integers.html (417.60 KB)
- 📄 113 Lonely Integer.html (433.17 KB)
- 📄 114 Swap Odd and Even Bits.html (979.16 KB)
- 📄 115 Introduction to Math and Geometry.html (229.97 KB)
- 📄 116 Spiral Traversal.html (1.38 MB)
- 📄 117 Reverse 32-Bit Integer.html (1.06 MB)
- 📄 118 Maximum Collinear Points.html (928.82 KB)
- 📄 119 The Josephus Problem.html (372.43 KB)
- 📄 120 Triangle Numbers.html (1.12 MB)
- 📄 names.txt (3.75 KB)
- 📂 Generative AI System Design Interview
- 📄 001 Introduction and Overview.html (930.80 KB)
- 📄 002 Gmail Smart Compose.html (2.11 MB)
- 📄 003 Google Translate.html (1.46 MB)
- 📄 004 ChatGPT Personal Assistant Chatbot.html (1.57 MB)
- 📄 005 Image Captioning.html (962.11 KB)
- 📄 006 Retrieval-Augmented Generation.html (2.15 MB)
- 📄 007 Realistic Face Generation.html (4.12 MB)
- 📄 008 High-Resolution Image Synthesis.html (1.12 MB)
- 📄 009 Text-to-Image Generation.html (5.86 MB)
- 📄 010 Personalized Headshot Generation.html (2.55 MB)
- 📄 011 Text-to-Video Generation.html (3.93 MB)
- 📄 names.txt (361.00 B)
- 📂 How to Write a Good Resume
- 📄 001 Acknowledgements.html (115.93 KB)
- 📄 002 Introduction.html (122.53 KB)
- 📄 003 PART 1 RESUMES AND THE HIRING PROCESS.html (115.88 KB)
- 📄 004 Chapter 1 Why Resumes and CVs are Important.html (133.91 KB)
- 📄 005 Chapter 2 The Hiring Pipeline.html (439.49 KB)
- 📄 006 PART 2 WRITING THE RESUME.html (117.08 KB)
- 📄 007 Chapter 3 Tech Resume Basics.html (219.66 KB)
- 📄 008 Chapter 4 Resume Structure.html (491.83 KB)
- 📄 009 Chapter 5 Standing Out.html (986.04 KB)
- 📄 010 Chapter 6 Common Mistakes.html (635.32 KB)
- 📄 011 Chapter 7 Different Experience Levels, Different Career Paths.html (508.04 KB)
- 📄 012 Chapter 8 Exercises to Polish Your Resume.html (194.40 KB)
- 📄 013 Chapter 9 Beyond the Resume.html (401.58 KB)
- 📄 014 PART 3 EXAMPLES AND INSPIRATION.html (116.22 KB)
- 📄 015 Chapter 10 Good Resume Template Principles.html (610.12 KB)
- 📄 016 Chapter 11 Resume Templates.html (1.29 MB)
- 📄 017 Chapter 12 Resume Improvement Examples.html (2.02 MB)
- 📄 018 Chapter 13 Advice for Hiring Managers on Running a Good Screening Process.html (137.66 KB)
- 📄 019 Conclusion.html (115.46 KB)
- 📂 Machine Learning System Design Interview
- 📄 01. Introduction and Overview.html (1.34 MB)
- 📄 02. Visual Search System.html (1.68 MB)
- 📄 03. Google Street View Blurring System.html (1.26 MB)
- 📄 04. YouTube Video Search.html (1.33 MB)
- 📄 05.Harmful Content Detection.html (1.41 MB)
- 📄 06. Video Recommendation System.html (1.56 MB)
- 📄 07. Event Recommendation System.html (1.43 MB)
- 📄 08. Ad Click Prediction on Social Platforms.html (1.65 MB)
- 📄 09. Similar Listings on Vacation Rental Platforms.html (1.18 MB)
- 📄 10. Personalized News Feed.html (1.23 MB)
- 📄 11. People You May Know.html (1.31 MB)
- 📂 Mobile System Design Interview
- 📄 001 Introduction.html (288.73 KB)
- 📄 002 A framework for Mobile SD interviews.html (465.25 KB)
- 📄 003 News feed app.html (1.37 MB)
- 📄 004 Chat app.html (2.34 MB)
- 📄 005 Stock trading app.html (1.08 MB)
- 📄 006 Pagination library.html (504.10 KB)
- 📄 007 Hotel reservation app.html (1.20 MB)
- 📄 008 Google Drive app.html (1.17 MB)
- 📄 009 YouTube app.html (788.34 KB)
- 📄 010 Mobile System Design Building Blocks.html (2.32 MB)
- 📄 011 Quick Reference Cheat Sheet for MSD Interview.html (117.85 KB)
- 📄 names.txt (297.00 B)
- 📂 Object-Oriented Design Interview
- 📄 001 What is an Object-Oriented Design Interview.html (521.02 KB)
- 📄 002 A Framework for the OOD Interview.html (288.77 KB)
- 📄 003 OOP Fundamentals.html (1.63 MB)
- 📄 004 Design a Parking Lot.html (1.59 MB)
- 📄 005 Design a Movie Ticket Booking System.html (2.21 MB)
- 📄 006 Design a Unix File Search System.html (808.26 KB)
- 📄 007 Design a Vending Machine.html (501.81 KB)
- 📄 008 Design an Elevator System.html (258.61 KB)
- 📄 009 Design a Grocery Store System.html (2.18 MB)
- 📄 010 Design a Tic Tac Toe Game.html (260.27 KB)
- 📄 011 Design a Blackjack Game.html (386.79 KB)
- 📄 012 Design a Shipping Locker System.html (1.74 MB)
- 📄 013 Design an ATM System.html (450.71 KB)
- 📄 014 Design a Restaurant Management System.html (2.21 MB)
- 📄 names.txt (476.00 B)
- 📂 System Design Interview
- 📄 0. Foreword.html (3.21 MB)
- 📄 1. Join the Community.html (3.21 MB)
- 📄 10. Design A Web Crawler.html (3.89 MB)
- 📄 11. Design A Notification System.html (6.10 MB)
- 📄 12. Design A News Feed System.html (3.98 MB)
- 📄 13. Design A Chat System.html (3.64 MB)
- 📄 14. Design A Search Autocomplete System.html (4.29 MB)
- 📄 15. Design YouTube.html (6.45 MB)
- 📄 16. Design Google Drive.html (4.74 MB)
- 📄 17. Proximity Service.html (4.26 MB)
- 📄 18. Nearby Friends.html (4.11 MB)
- 📄 19. Google Maps.html (7.16 MB)
- 📄 2. Scale From Zero To Millions Of Users.html (4.04 MB)
- 📄 20. Distributed Message Queue.html (4.22 MB)
- 📄 21. Metrics Monitoring and Alerting System.html (3.88 MB)
- 📄 22. Ad Click Event Aggregation.html (4.11 MB)
- 📄 23. Hotel Reservation System.html (3.82 MB)
- 📄 24. Distributed Email Service.html (3.87 MB)
- 📄 25. S3-like Object Storage.html (4.67 MB)
- 📄 26. Real-time Gaming Leaderboard.html (4.01 MB)
- 📄 27. Payment System.html (3.70 MB)
- 📄 28. Digital Wallet.html (4.38 MB)
- 📄 29. Stock Exchange.html (4.44 MB)
- 📄 3. Back-of-the-envelope Estimation.html (3.77 MB)
- 📄 30. The Learning Continues.html (3.36 MB)
- 📄 4. A Framework For System Design Interviews.html (3.38 MB)
- 📄 5. Design A Rate Limiter.html (3.63 MB)
- 📄 6. Design Consistent Hashing.html (3.54 MB)
- 📄 7. Design A Key-value Store.html (3.69 MB)
- 📄 8. Design A Unique ID Generator In Distributed Systems.html (3.43 MB)
- 📄 9. Design A URL Shortener.html (4.01 MB)
📂 Code & Materials
- 📄 Chat History Deep Dive.txt (21.47 KB)
- 📄 WEEK 6 Additional Links.zip (1.40 MB)
- 📄 WEEK 6 Capstone Project Guidelines.pdf (103.06 KB)
- 📄 WEEK 6 Chat History Deep Dive.txt (50.31 KB)
- 📄 WEEK 6 Demo 1 Chat History.txt (36.86 KB)
- 📄 Week 1 Guided Learning LLM Foundations.txt (2.72 KB)
- 📄 Week 1 Project 1 Build an LLM Playground.txt (2.01 KB)
- 📄 Week 2 Guided Learning Retrieval Augmented Generation (RAG).txt (2.21 KB)
- 📄 Week 2 Project 2 Build a Customer Support Chatbot.txt (1.90 KB)
- 📄 Week 3 Guided Learning Agents.txt (2.27 KB)
- 📄 Week 3 Project 3 Build an “Ask-the-Web” Agent Similar to Perplexity with Tool Calling.txt (1.78 KB)
- 📄 Week 4 Guided Learning Thinking and Reasoning LLMs.txt (2.03 KB)
- 📄 Week 4 Project 4 Build “Deep Research” Capability with Web Search and Reasoning Models.txt (1.85 KB)
- 📄 Week 5 Guided Learning Image and Video Generation.txt (3.20 KB)
- 📄 Week 5 Project 5 Build a Multi-Modal Generation Agent.txt (1.77 KB)
- 📄 multimodal_agent_solution.ipynb (6.51 MB)
- 📄 p1.excalidraw (11.57 MB)
- 📄 p2.excalidraw (7.51 MB)
- 📄 p3.excalidraw (10.78 MB)
- 📄 p4.excalidraw (2.31 MB)
- 📄 p5.excalidraw (12.51 MB)
📂 Week 1
📄 001 WEEK 1 Introduction and Logistics, Sat 104 10-1130 AM (PT).mp4 (841.33 MB)
📄 002 WEEK 1 Guided Learning LLM Foundations.mp4 (609.21 MB)
📂 Week 2
📄 003 WEEK 2 Deep Dive Project 1 Build an LLM Playground, Sat 1011 10-1130 AM (PT).mp4 (1.27 GB)
📄 004 WEEK 2 Guided Learning Retrieval Augmented Generation (RAG).mp4 (343.35 MB)
📂 Week 3
📄 005 WEEK 3 Deep-Dive Project 2 Build a Customer Support Chatbot, Sat 1018 10-1130 AM (PT).mp4 (379.12 MB)
📄 006 WEEK 3 Guided Learning Agents.mp4 (483.72 MB)
📂 Week 4
📄 007 WEEK 4 Deep-Dive Project 3 Build an “Ask-the-Web” Agent Similar to Perplexity, Sat 1025 10-1130 AM (PT).mp4 (453.31 MB)
📄 008 WEEK 4 Guided Learning Thinking and Reasoning LLMs.mp4 (446.65 MB)
📂 Week 5
📄 0010 WEEK 5 Guided Learning Image and Video Generation.mp4 (532.78 MB)
📄 009 WEEK 5 Deep-Dive Project 4 Build “Deep Research” Capability, Sat 111 10-1130 AM (PT).mp4 (411.04 MB)
📂 Week 6
📄 0011 WEEK 6 Deep-Dive Project 5 Build a Multi-modal Generation Agent, Sat 118 10-1130 AM (PT).mp4 (427.78 MB)
📄 0012 WEEK 6 Capstone Project Demo and Presentation, Sun 119 10 AM -12 PM (PT).mp4 (472.96 MB)
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