Merge pull request #1038 from marcelpetrick/mpe/typoFixes

leestott · web-flow · commit 6bc5901416e4 · 2025-11-18T16:43:53.000Z
fix(docs): correct typos found during code review
diff --git a/00-course-setup/02-setup-local.md b/00-course-setup/02-setup-local.md
@@ -213,5 +213,5 @@ Full provider instructions live in [`providers.md`](03-providers.md).
 | Docker build fails *No space left*        | Docker Desktop ▸ *Settings* ▸ *Resources* → increase disk size. |
 | VS Code keeps prompting to reopen         | You may have both Options active; choose one (venv **or** container)|
 | OpenAI 401 / 429 errors                   | Check `OPENAI_API_KEY` value / request rate limits.             |
-| Errors using Conda                        | Install Microsft AI libraries using `conda install -c microsoft azure-ai-ml`|
+| Errors using Conda                        | Install Microsoft AI libraries using `conda install -c microsoft azure-ai-ml`|
 
diff --git a/00-course-setup/03-providers.md b/00-course-setup/03-providers.md
@@ -97,7 +97,7 @@ This will take you to the Azure OpenAI Studio website, where we'll find the othe
 1. You will need a _text-generation_ model - we recommend: **gpt-35-turbo**
 1. You will need a _text-embedding_ model - we recommend **text-embedding-ada-002**
 
-Now update the environment variables to reflect the _Deployment name_ used. This will typically be the same as the model name unless you changed it explcitly. So, as an example, you might have:
+Now update the environment variables to reflect the _Deployment name_ used. This will typically be the same as the model name unless you changed it explicitly. So, as an example, you might have:
 
 ```bash
 AZURE_OPENAI_DEPLOYMENT='gpt-35-turbo'
diff --git a/07-building-chat-applications/python/aoai-assignment.ipynb b/07-building-chat-applications/python/aoai-assignment.ipynb
@@ -631,7 +631,7 @@
       },
       "source": [
         "## Embeddings\n",
-        "This section will show how to retrieve embeddings, and find similarities between words, sentences, and documents. In order to run the following noteboooks you need to deploy a model that uses `text-embedding-ada-002` as base model and set his deployment name inside .env file, using the `AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT` variable."
+        "This section will show how to retrieve embeddings, and find similarities between words, sentences, and documents. In order to run the following notebooks you need to deploy a model that uses `text-embedding-ada-002` as base model and set his deployment name inside .env file, using the `AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT` variable."
       ]
     },
     {
diff --git a/07-building-chat-applications/typescript/chat-completions-app/src/main.ts b/07-building-chat-applications/typescript/chat-completions-app/src/main.ts
@@ -26,7 +26,7 @@ export async function main() {
             console.log(choice.message);
         }
     } catch (error) {
-        console.log("The sample encoutered an error: ", error);
+        console.log("The sample encountered an error: ", error);
     }
 }
 
diff --git a/08-building-search-applications/python/aoai-solution.ipynb b/08-building-search-applications/python/aoai-solution.ipynb
@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "In order to run the following noteboooks, if you haven't done yet, you need to deploy a model that uses `text-embedding-ada-002` as base model and set the deployment name inside .env file as `AZURE_OPENAI_EMBEDDINGS_ENDPOINT`"
+    "In order to run the following notebooks, if you haven't done yet, you need to deploy a model that uses `text-embedding-ada-002` as base model and set the deployment name inside .env file as `AZURE_OPENAI_EMBEDDINGS_ENDPOINT`"
    ]
   },
   {
@@ -163,7 +163,7 @@
    "source": [
     "pd_vectors = load_dataset(DATASET_NAME)\n",
     "\n",
-    "# get user query from imput\n",
+    "# get user query from input\n",
     "while True:\n",
     "    query = input(\"Enter a query: \")\n",
     "    if query == \"exit\":\n",
diff --git a/08-building-search-applications/python/oai-solution.ipynb b/08-building-search-applications/python/oai-solution.ipynb
@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "In order to run the following noteboooks, if you haven't done yet, you need to set the openai key inside .env file as `OPENAI_API_KEY`"
+    "In order to run the following notebooks, if you haven't done yet, you need to set the openai key inside .env file as `OPENAI_API_KEY`"
    ]
   },
   {
@@ -161,7 +161,7 @@
    "source": [
     "pd_vectors = load_dataset(DATASET_NAME)\n",
     "\n",
-    "# get user query from imput\n",
+    "# get user query from input\n",
     "while True:\n",
     "    query = input(\"Enter a query: \")\n",
     "    if query == \"exit\":\n",
diff --git a/11-integrating-with-function-calling/python/oai-assignment.ipynb b/11-integrating-with-function-calling/python/oai-assignment.ipynb
@@ -84,7 +84,7 @@
    "source": [
     "student_1_description=\"Emily Johnson is a sophomore majoring in computer science at Duke University. She has a 3.7 GPA. Emily is an active member of the university's Chess Club and Debate Team. She hopes to pursue a career in software engineering after graduating.\"\n",
     " \n",
-    "student_2_description = \"Michael Lee is a sophomore majoring in computer science at Stanford University. He has a 3.8 GPA. Michael is known for his programming skills and is an active member of the university's Robotics Club. He hopes to pursue a career in artificial intelligence after finshing his studies.\""
+    "student_2_description = \"Michael Lee is a sophomore majoring in computer science at Stanford University. He has a 3.8 GPA. Michael is known for his programming skills and is an active member of the university's Robotics Club. He hopes to pursue a career in artificial intelligence after finishing his studies.\""
    ]
   },
   {
diff --git a/14-the-generative-ai-application-lifecycle/README.md b/14-the-generative-ai-application-lifecycle/README.md
@@ -37,7 +37,7 @@ First, to understand the lifecycle and the modifications, let's note the next in
 
 ![LLMOps infographic](./images/02-llmops.png?WT.mc_id=academic-105485-koreys)
 
-As you may note, this is different from the usual Lifecycles from MLOps. LLMs have many new requirements, as Prompting, different techniques to improve quality (Fine-Tuning, RAG, Meta-Prompts), different assessment and responsability with responsible AI, lastly, new evaluation metrics (Quality, Harm, Honesty, Cost and Latency).
+As you may note, this is different from the usual Lifecycles from MLOps. LLMs have many new requirements, as Prompting, different techniques to improve quality (Fine-Tuning, RAG, Meta-Prompts), different assessment and responsibility with responsible AI, lastly, new evaluation metrics (Quality, Harm, Honesty, Cost and Latency).
 
 For instance, take a look at how we ideate. Using prompt engineering to experiment with various LLMs to explore possibilities to test if their Hypothesis could be correct.
 
diff --git a/15-rag-and-vector-databases/notebook-rag-vector-databases.ipynb b/15-rag-and-vector-databases/notebook-rag-vector-databases.ipynb
@@ -2606,7 +2606,7 @@
    "source": [
     "# Retrieval\n",
     "\n",
-    "Vector search and similiarity between our prompt and the database"
+    "Vector search and similarity between our prompt and the database"
    ]
   },
   {
diff --git a/16-open-source-models/README.md b/16-open-source-models/README.md
@@ -66,7 +66,7 @@ There is no one answer for choosing an open model. A good place to start is by u
 When looking to compare LLMs across the different types, [Artificial Analysis](https://artificialanalysis.ai/?WT.mc_id=academic-105485-koreyst) is another great resource:
 
 ![Model Quality](./images/model-quality.png?WT.mc_id=academic-105485-koreyst)
-Source: Artifical Analysis
+Source: Artificial Analysis
 
 If working on a specific use case, searching for fine-tuned versions that are focused on the same area can be effective. Experimenting with multiple open models to see how they perform according to your and your users' expectations is another good practice
 
diff --git a/18-fine-tuning/python/openai/oai-assignment.ipynb b/18-fine-tuning/python/openai/oai-assignment.ipynb
@@ -262,7 +262,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "You can also view the status by visiting the OpenAI website and exploring the _Fine-tuning_ section of the platform. This will show you the status of the current job, and also let you track the history of prior job execution runs. In this screenshot, you can see that the prior execution failed, and the second run succeeeded. For context, this happened when the first run used a JSON file with incorrectly formatted records  - once fixed, the second run completed successfully and made the model available for use.\n",
+    "You can also view the status by visiting the OpenAI website and exploring the _Fine-tuning_ section of the platform. This will show you the status of the current job, and also let you track the history of prior job execution runs. In this screenshot, you can see that the prior execution failed, and the second run succeeded. For context, this happened when the first run used a JSON file with incorrectly formatted records  - once fixed, the second run completed successfully and made the model available for use.\n",
     "\n",
     "![Fine-tuning job status](./img/fine-tuned-model-status.png?WT.mc_id=academic-105485-koreyst)"
    ]
diff --git a/19-slm/python/phi35_moe_demo.ipynb b/19-slm/python/phi35_moe_demo.ipynb
@@ -332,7 +332,7 @@
         "\n",
         "```\n",
         "\n",
-        "Remember just output the final result, ouput in JSON format containing `\"agentid\"`,`\"tool_name\"` , `\"input\"` and `\"output\"`  key-value pairs .:\n",
+        "Remember just output the final result, output in JSON format containing `\"agentid\"`,`\"tool_name\"` , `\"input\"` and `\"output\"`  key-value pairs .:\n",
         "\n",
         "```json\n",
         "\n",
@@ -458,7 +458,7 @@
           "output_type": "execute_result",
           "execution_count": 16,
           "data": {
-            "text/plain": "'<|system|> You are a helpful AI assistant, you are an agent capable of using a variety of tools to answer a question. Here are a few of the tools available to you:\\n\\n- Blog: This tool helps you describe a certain knowledge point and content, and finally write it into Twitter or Facebook style content\\n- Translate: This is a tool that helps you translate into any language, using plain language as required\\n\\nTo use these tools you must always respond in JSON format containing `\"tool_name\"` and `\"input\"` key-value pairs. For example, to answer the question, \"Build Muliti Agents with MOE models\" you must use the calculator tool like so:\\n\\n```json\\n\\n{\\n    \"tool_name\": \"Blog\",\\n    \"input\": \"Build Muliti Agents with MOE models\"\\n}\\n\\n```\\n\\nOr to translate the question \"can you introduce yourself in Chinese\" you must respond:\\n\\n```json\\n\\n{\\n    \"tool_name\": \"Search\",\\n    \"input\": \"can you introduce yourself in Chinese\"\\n}\\n\\n```\\n\\nRemember just output the final result, ouput in JSON format containing `\"agentid\"`,`\"tool_name\"` , `\"input\"` and `\"output\"`  key-value pairs .:\\n\\n```json\\n\\n[\\n\\n\\n{   \"agentid\": \"step1\",\\n    \"tool_name\": \"Blog\",\\n    \"input\": \"Build Muliti Agents with MOE models\",\\n    \"output\": \".........\"\\n},\\n\\n{   \"agentid\": \"step2\",\\n    \"tool_name\": \"Search\",\\n    \"input\": \"can you introduce yourself in Chinese\",\\n    \"output\": \".........\"\\n},\\n{\\n    \"agentid\": \"final\"\\n    \"tool_name\": \"Result\",\\n    \"output\": \".........\"\\n}\\n]\\n\\n```\\n\\nThe users answer is as follows.\\n <|end|>\\n<|user|> Write something about Generative AI with MOE , translate it to Chinese <|end|>\\n<|assistant|>'"
+            "text/plain": "'<|system|> You are a helpful AI assistant, you are an agent capable of using a variety of tools to answer a question. Here are a few of the tools available to you:\\n\\n- Blog: This tool helps you describe a certain knowledge point and content, and finally write it into Twitter or Facebook style content\\n- Translate: This is a tool that helps you translate into any language, using plain language as required\\n\\nTo use these tools you must always respond in JSON format containing `\"tool_name\"` and `\"input\"` key-value pairs. For example, to answer the question, \"Build Muliti Agents with MOE models\" you must use the calculator tool like so:\\n\\n```json\\n\\n{\\n    \"tool_name\": \"Blog\",\\n    \"input\": \"Build Muliti Agents with MOE models\"\\n}\\n\\n```\\n\\nOr to translate the question \"can you introduce yourself in Chinese\" you must respond:\\n\\n```json\\n\\n{\\n    \"tool_name\": \"Search\",\\n    \"input\": \"can you introduce yourself in Chinese\"\\n}\\n\\n```\\n\\nRemember just output the final result, output in JSON format containing `\"agentid\"`,`\"tool_name\"` , `\"input\"` and `\"output\"`  key-value pairs .:\\n\\n```json\\n\\n[\\n\\n\\n{   \"agentid\": \"step1\",\\n    \"tool_name\": \"Blog\",\\n    \"input\": \"Build Muliti Agents with MOE models\",\\n    \"output\": \".........\"\\n},\\n\\n{   \"agentid\": \"step2\",\\n    \"tool_name\": \"Search\",\\n    \"input\": \"can you introduce yourself in Chinese\",\\n    \"output\": \".........\"\\n},\\n{\\n    \"agentid\": \"final\"\\n    \"tool_name\": \"Result\",\\n    \"output\": \".........\"\\n}\\n]\\n\\n```\\n\\nThe users answer is as follows.\\n <|end|>\\n<|user|> Write something about Generative AI with MOE , translate it to Chinese <|end|>\\n<|assistant|>'"
           },
           "metadata": {}
         }
diff --git a/20-mistral/python/githubmodels-assignment.ipynb b/20-mistral/python/githubmodels-assignment.ipynb
@@ -210,7 +210,7 @@
     "\n",
     "To show differences in latency between Mistral Small and Large, run the below cells. \n",
     "\n",
-    "You should see a difference in response times between 3-5 seconds. Also not the response lengths and style over the smae prompt.  "
+    "You should see a difference in response times between 3-5 seconds. Also not the response lengths and style over the same prompt.  "
    ]
   },
   {
@@ -323,7 +323,7 @@
     "\n",
     "In this sample, we will look at how Mistral NeMo handles tokenization compared to Mistral Large. \n",
     "\n",
-    "Both samples take the same prompt but you shoud see that NeMo returns back less tokens vs Mistral Large. "
+    "Both samples take the same prompt but you should see that NeMo returns back less tokens vs Mistral Large. "
    ]
   },
   {

Original file line number	Diff line number	Diff line change
`@@ -631,7 +631,7 @@`
`631`	`631`	`},`
`632`	`632`	`"source": [`
`633`	`633`	`"## Embeddings\n",`
`634`		- "This section will show how to retrieve embeddings, and find similarities between words, sentences, and documents. In order to run the following noteboooks you need to deploy a model that uses `text-embedding-ada-002` as base model and set his deployment name inside .env file, using the `AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT` variable."
	`634`	+ "This section will show how to retrieve embeddings, and find similarities between words, sentences, and documents. In order to run the following notebooks you need to deploy a model that uses `text-embedding-ada-002` as base model and set his deployment name inside .env file, using the `AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT` variable."
`635`	`635`	`]`
`636`	`636`	`},`
`637`	`637`	`{`
Original file line number	Diff line number	Diff line change
`@@ -26,7 +26,7 @@ export async function main() {`
`26`	`26`	`console.log(choice.message);`
`27`	`27`	`}`
`28`	`28`	`} catch (error) {`
`29`		`- console.log("The sample encoutered an error: ", error);`
	`29`	`+ console.log("The sample encountered an error: ", error);`
`30`	`30`	`}`
`31`	`31`	`}`
`32`	`32`
Original file line number	Diff line number	Diff line change
`@@ -84,7 +84,7 @@`
`84`	`84`	`"source": [`
`85`	`85`	`"student_1_description=\"Emily Johnson is a sophomore majoring in computer science at Duke University. She has a 3.7 GPA. Emily is an active member of the university's Chess Club and Debate Team. She hopes to pursue a career in software engineering after graduating.\"\n",`
`86`	`86`	`" \n",`
`87`		`- "student_2_description = \"Michael Lee is a sophomore majoring in computer science at Stanford University. He has a 3.8 GPA. Michael is known for his programming skills and is an active member of the university's Robotics Club. He hopes to pursue a career in artificial intelligence after finshing his studies.\""`
	`87`	`+ "student_2_description = \"Michael Lee is a sophomore majoring in computer science at Stanford University. He has a 3.8 GPA. Michael is known for his programming skills and is an active member of the university's Robotics Club. He hopes to pursue a career in artificial intelligence after finishing his studies.\""`
`88`	`88`	`]`
`89`	`89`	`},`
`90`	`90`	`{`
Original file line number	Diff line number	Diff line change
`@@ -2606,7 +2606,7 @@`
`2606`	`2606`	`"source": [`
`2607`	`2607`	`"# Retrieval\n",`
`2608`	`2608`	`"\n",`
`2609`		`- "Vector search and similiarity between our prompt and the database"`
	`2609`	`+ "Vector search and similarity between our prompt and the database"`
`2610`	`2610`	`]`
`2611`	`2611`	`},`
`2612`	`2612`	`{`