ZeroToMastery-AIEngineeringBootcampBuildingAIApplications(LangChain,LLMAPIsandmore)2025-8

Course content

Sections: 1

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Activities: 1

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Resources: 181

Announcements
1 AI Engineering Bootcamp Building AI Applications with LLM APIs LangChain much moreUsing Jupyter Notebook
2 Using Jupyter Notebook
3 Using Virtual Environments _venv_ 454K
4 Getting Started with the requests and httpx Libraries in Python 318K
5 Handling HTTP Errors 329K
6 Managing HTTP Authentication and Headers _OpenAI API_ 336K
7 Setting Up the Environment Jupyter Notebook and Pandas 556K
8 Introduction to Pandas Series and DataFrames 250K
9 Importing and Exporting Data Working with CSV Files 319K
10 Exporting Data to Different Formats Excel_ JSON_ SQL_ YAML 384K
11 Modifying Data Adding and Dropping Columns and Rows 218K
12 Accessing Data Using dfiloc__ and dfloc__ 244K
13 Sampling and Previewing Data Using dfsample__ and dfhead__ 299K
14 Filtering Data Masks and pandasSeriesbetween__ 236K
15 Sorting Data Understanding Pandas Sorting Methods 224K
16 Handling Missing Data 268K
17 Aggregations and Grouping Data 290K
18 Project Analyzing Website Traffic Data 236K
19 Time Series Data Manipulation in Pandas 253K
20 Foundations of LLMs and Generative AI 452K
21 Tokens_ Context Windows and Cost 304K
22 Exploring LLM APIs AI as a Service 407K
23 OpenAI Playground_ Google AI Studio_ and Anthropic Workbench 408K
24 Challenges and Limitations of LLMs 281K
25 The State of AI Present and Future The Good and the Bad 383K
26 Pretraining Data _Internet_ 1172K
27 Tokenization 1053K
28 Training the Neural Network 496K
29 Post Training Supervised Fine Tuning _SFT_ and Reinforcement Learning _RL_ 419K
30 Reinforcement Learning _RL_ 351K
31 Becoming Better than Humans AGI and ASI with RL 410K
32 Reinforcement Learning with Human Feedback _RLHF_ 379K
33 How to Deal With Hallucinations 354K
34 Using Tools Internet Search_ Interpreter_ and Deep Search 359K
35 Big Ideas Recap _Core Summary_ 366K
36 Authenticating to OpenAI using Python Dotenv 444K
37 Chat Completions Endpoint 440K
38 Developer Message 449K
39 Streaming API Responses 569K
40 Using Local Base64 Images as Input 398K
41 Using Online Images as Input 473K
42 Chat Completion API Parameters Temperature and Seed 829K
43 Chat Completion API Parameters Top P_ Max_Tokens_ Penalties 610K
44 Diving into OpenAIs Reasoning Models _o1 and o3_ 401K
45 Best Practices for Prompting Reasoning Models 424K
46 Transcriptions with Whisper 849K
47 Translations with Whisper 728K
48 Text to Speech _TTS_ API 370K
49 Generating Original Images Using the DALL E 3 502K
50 Creating Variations of Images with DALL E 376K
51 Editing Images with DALL E 640K
52 Intro to Prompt Engineering 577K
53 Tactic 1 Position Instruction Clearly with Delimiters 471K
54 Tactic 2 Provide Detailed Instructions for the Context 630K
55 Tactic 3 Use the Rich Text Format _RTF_ 577K
56 Tactic 4 Few Shot Prompting 675K
57 Tactic 5 Specify the Steps Required to Complete a Task 650K
58 Tactic 6 Give Models Time to Think 636K
59 Other Tactics and Principles for Better Prompting 559K
60 Avoid Hallucinations Using Guarding 615K
61 Summary 521K
62 Project Introduction 918K
63 Creating a Daily Meal Plan Using OpenAI API 326K
64 Creating the Prompt 560K
65 Running the Program 890K
66 Generating Original Images for the Recipes using DALL E 565K
67 Narrate the Meals using the Text to Speech Model 910K
68 Setting Up the Python SDK and Authenticating for Gemini API 426K
69 Generating Text From Text Prompts 549K
70 Streaming Gemini Responses 625K
71 Generating Text From Images 396K
72 Gemini API Generation Parameters Controlling How the Model Generates Responses 482K
73 Gemini API Generation Parameters Explained 426K
74 Building Chat Conversations 538K
75 Project Building a Conversational Agent Using Gemini Pro 367K
76 System Instructions 418K
77 The File API Prompting with Media Files 577K
78 Tokens 367K
79 Prompting with Audio 545K
80 Project Requirements 434K
81 Building the Application 379K
82 Testing the Application 448K
83 Streamlit Transform Your Jupyter Notebooks into Interactive Web Apps 616K
84 Creating the Web App Layout With Streamlit 375K
85 Saving and Displaying the History Using the Streamlit Session State 376K
86 Exercise Imposter Syndrome 931K
87 Project Introduction 698K
88 Getting Images Using a Generator 266K
89 Renaming Images Using Gemini 414K
90 LangChain Demo 725K
91 Introduction to LangChain 291K
92 Working with the OpenAI Models 359K
93 Caching LLM Responses 345K
94 LLM Streaming 329K
95 Prompt Templates 307K
96 ChatPromptTemplate 448K
97 Understanding Chains 438K
98 Installing the Python Libraries for Gemini and Authenticating to Gemini 503K
99 Integrating Gemini with LangChain 530K
100 Using a System Prompt and Enabling Streaming 453K
101 Multimodal AI With Gemini 344K
102 LangChain Tools DuckDuckGo and Wikipedia 490K
103 Creating a React Agent 435K
104 Testing the React Agent 685K
105 Intro to OpenAI_s Text Embeddings 443K
106 Generating Simple Embeddings 411K
107 Embedding the Dataset for Similarity Searches 454K
108 Estimating Embedding Costs With Tiktoken 341K
109 Performing Semantic Searches 457K
110 Project Introduction
111 Loading Your Custom _Private_ PDF Documents
112 Loading Different Document Formats
113 Public and Private Service Loaders 447K
114 Chunking Strategies and Splitting the Documents 349K
115 Intro to Vector Stores and Authenticating to Pinecone 387K
116 Working with Pinecone Indexes 359K
117 Working with Vectors 435K
118 Pinecone Namespaces 376K
119 Embedding and Uploading to a Vector Database _Pinecone_ 419K
120 Asking and Getting Answers
121 Using Chroma as a Vector DB 494K
122 Adding Memory to the RAG System _Chat History_ 430K
123 Using a Custom Prompt 596K
124 Introduction to Agents and ReAct 370K
125 Creating the Agent Class 382K
126 Creating the ReAct Prompt 585K
127 Creating the Tools 487K
128 Testing the Agent 521K
129 Automating the Agent 451K
130 LangGraph Concepts and Core Components 321K
131 Building a Chatbot 317K
132 Visualizing the Graph 313K
133 Running the Chatbot 357K
134 Tavily AI 563K
135 Enhancing the ChatBot with Tools 538K
136 Adding Memory to the Chatbot 510K
137 Intro to Reflection 323K
138 Generate 401K
139 Reflect and Repeat 541K
140 Define the Graph Part 1
141 Define the Graph Part 2 478K
142 Running the App 710K
143 Intro to LangSmith 556K
144 Setting Up LangSmith 799K
145 Tracing with LangSmith 369K
146 Tracing the Reflective Agentic App 662K
147 Project Overview 165K
148 Defining the Agent State and the Prompts 423K
149 Implementing Agents and Nodes 376K
150 Defining the Conditional Edge 315K
151 Defining the Graph 358K
152 Running the App 770K
153 Tracing the App with LangSmith 633K
154 Note 567K
155 Application Overview 624K
156 Extracting Data from ArXiv with Pandas 540K
157 Downloading Research Papers 594K
158 Loading_ Splitting and Expanding Data
159 Building a Knowledge Base for RAG 493K
160 Creating a Pinecone Index 504K
161 Loading the Knowledge Base and Deploying to Pinecone
162 Developing Custom Tools 208K
163 Implementing the ArXiv Fetch Tool 455K
164 Unlocking Web Search with Google SerpAPI 496K
165 Building Google SerpAPI Tools 405K
166 Creating RAG Tools 370K
167 Implementing the Final Answer Generation Tool 526K
168 06_14 Initializing the Oracle LLM 348K
169 Testing the Ecosystem 543K
170 Building a Decision Making Pipeline
171 Defining the Agent State 267K
172 Defining the Graph 405K
173 Generating Reports 1164K
174 Building the Final Research Report 646K
175 Concluding the Project 774K
176 Understanding Python Modules 281K
177 The OS Module 375K
178 Advanced Import Techniques and Best Practices 297K
179 Using __name__ __ ___main___ for Modular and Reusable Code 331K
180 Mastering Python Package Management with pip 351K
181 Thank You_