feat: LC-498 lesson video

apps/api/src/courses/course.service.ts

@@ -427,7 +427,7 @@ export class CourseService {
       )
       .orderBy(chapters.displayOrder);
 
-    // TODO: temporary firx
+    // TODO: temporary fix
     const getImageUrl = async (url: string) => {
       if (!url || url.startsWith("https://")) return url ?? "";
       return await this.fileService.getFileUrl(url);

apps/api/src/lesson/lesson.controller.ts

@@ -1,4 +1,14 @@
-import { Body, Controller, Delete, Get, Param, Patch, Post, Query, UseGuards } from "@nestjs/common";
+import {
+  Body,
+  Controller,
+  Delete,
+  Get,
+  Param,
+  Patch,
+  Post,
+  Query,
+  UseGuards,
+} from "@nestjs/common";
 import { Type } from "@sinclair/typebox";
 import { Validate } from "nestjs-typebox";
 

apps/api/src/scorm/services/scorm.service.ts

@@ -1,7 +1,7 @@
 import { randomUUID } from "crypto";
 import path from "path";
 
-import { Injectable, Inject, BadRequestException, NotFoundException } from "@nestjs/common";
+import { BadRequestException, Inject, Injectable, NotFoundException } from "@nestjs/common";
 import AdmZip from "adm-zip";
 import { JSDOM } from "jsdom";
 import { match } from "ts-pattern";

apps/api/src/seed/nice-data-seeds.ts

@@ -1607,7 +1607,7 @@ export const niceCourses: NiceCourseData[] = [
             type: LESSON_TYPES.TEXT,
             title: "Key Concepts and Terminologies in AI",
             description:
-              "<p>Artificial Intelligence (AI) refers to the simulation of human intelligence in machines programmed to think, learn, and make decisions. Below are some key concepts and terminologies essential to understanding AI:</p><ul><li><strong>Machine Learning (ML):</strong> A subset of AI focused on creating algorithms that allow computers to learn from and make predictions based on data. Example: A recommendation system suggesting movies based on your viewing history.</li><li><strong>Neural Networks:</strong> Inspired by the human brain, these are algorithms designed to recognize patterns and process data in layers, enabling tasks like image and speech recognition.</li><li><strong>Natural Language Processing (NLP):</strong> This involves teaching machines to understand, interpret, and generate human language.",
+              '<p>Artificial Intelligence (AI) refers to the simulation of human intelligence in machines programmed to think, learn, and make decisions. Below are some key concepts and terminologies essential to understanding AI:</p><ul><li><strong>Machine Learning (ML):</strong> A subset of AI focused on creating algorithms that allow computers to learn from and make predictions based on data. Example: A recommendation system suggesting movies based on your viewing history.</li><li><strong>Neural Networks:</strong> Inspired by the human brain, these are algorithms designed to recognize patterns and process data in layers, enabling tasks like image and speech recognition.</li><li><strong>Natural Language Processing (NLP):</strong> This involves teaching machines to understand, interpret, and generate human language. Example: Virtual assistants like Alexa or Siri.</li><li><strong>Computer Vision:</strong> A field of AI that enables computers to interpret and process visual data, such as images and videos. Example: Facial recognition technology.</li><li><strong>Deep Learning:</strong> A more complex subset of ML that uses large neural networks to analyze massive amounts of data and solve intricate problems, such as self-driving cars.</li><li><strong>Supervised vs. Unsupervised Learning:</strong><br>- <strong>Supervised Learning:</strong> The AI is trained on labeled data (e.g., images labeled as "cat" or "dog").<br>- <strong>Unsupervised Learning:</strong> The AI identifies patterns in unlabeled data without explicit instructions.</li><li><strong>Big Data:</strong> The large volume of structured and unstructured data generated by businesses and devices, which is essential for training AI models.</li><li><strong>Automation:</strong> AI is often used to automate repetitive tasks, freeing up human resources for more complex activities.</li><li><strong>Ethics in AI:</strong> As AI becomes more powerful, ensuring its ethical use (e.g., avoiding bias in decision-making) is critical for building trust.</li></ul><h3>Why These Concepts Matter</h3><p>Understanding these basic AI terms is the first step toward recognizing how AI can be applied in business. Each concept represents a building block of AI\'s potential to transform industries by increasing efficiency, improving decision-making, and creating innovative solutions.</p>',
             displayOrder: 2,
           },
           {

apps/api/src/storage/migrations/0006_incerase_lesson_description_characters_count.sql

@@ -0,0 +1 @@
+ALTER TABLE "lessons" ALTER COLUMN "description" SET DATA TYPE varchar(3000);