TLDR;
Alright, so this YouTube video by Marketing Fundas is basically an AI complete course for 2026 and beyond. It's designed to help you upgrade your skills and use AI in your business, profession, or personal life. The course is a mix of theory and practical stuff, teaching you how to use different AI tools, write blogs, build websites, create images and videos, and master prompt engineering.
- AI is a field in computer science focused on creating systems that mimic human intelligence.
- AI can perform tasks like learning, reasoning, problem-solving, perception, decision-making, and language understanding.
- There are different types of AI based on capabilities (ANI, AGI, ASI) and functionality (reactive machines, limited memory, theory of mind, self-aware AI).
AI Complete Course 2026 [0:00]
The Marketing Fundas team is bringing a course that's got both the theory and a whole lot of practical, like 80% practical. You'll get to grips with using AI tools on a practical level, with use case studies. You'll learn how to write blogs, create websites, make images and videos, and get a handle on prompt engineering. If you're keen to learn, drop a "Yes I am ready" in the comments. If the video gets over 1000 comments, they'll bring another powerful course.
Live AI and Digital Marketing Batches [2:23]
For those who prefer live learning and certification, Marketing Fundas is launching live AI and digital marketing batches. This is a three-month course with over 25 modules, live classes, doubt sessions, recordings, and certification. Industry experts will teach the course live. It's available for ₹4,999.
What is AI? [3:49]
AI is a field in computer science focused on creating systems or machines that perform tasks requiring human intelligence. This includes speaking, listening, understanding, learning, and making perceptions. The goal is to replicate these human abilities in AI, and technology is making progress in this area.
Tasks Performed by AI [5:34]
AI systems are designed to acquire knowledge and skills based on data and experiences. They can draw conclusions and make logical inferences. AI can solve complex problems by planning and navigating. AI systems can develop perceptions based on environmental information, like speech and computer vision, and adapt accordingly. AI can make decisions based on data, past experiences, and goals. For example, Amazon's AI system recommends products based on user history, and Siri makes recommendations based on user demands. AI can understand and generate language using techniques like Natural Language Processing (NLP), which empowers AI to create human-like language for chatting and translating. AI systems can also recognize images and patterns.
Types of AI and Techniques Used [10:12]
There are different types of AI based on capabilities: Artificial Narrow Intelligence (ANI), also known as weak AI; Artificial General Intelligence (AGI), also known as strong AI or human-level AI; and Artificial Super Intelligence (ASI). There are also types of AI based on functionality: reactive machines, limited memory, theory of mind (future AI), and self-aware AI (also future AI).
What is Computer Science? [12:08]
Computer science involves writing instructions (software), creating programs, and processing data. It includes fields like algorithms, data structures, AI, machine learning, computer graphics, software engineering, cybersecurity, databases, human-computer interaction, theoretical computer science, networks, operating systems, computer biology, embedded systems, robotics, and data science. These technologies empower businesses.
What is LLM? [15:22]
Large Language Models (LLMs) are AI techniques that use large amounts of text data to understand and generate language. LLMs are AI techniques that use large amounts of text data to understand and generate language. Examples include ChatGPT, Gemini, and Perplexity.
What is Generative AI? [19:08]
Generative AI is a type of AI that produces new content like text, images, music, and code. Unlike AI systems that analyze and classify existing data, generative AI learns patterns and structures from data to create original content. Generative AI models use deep learning techniques, particularly neural networks. Major technologies include Generative Adversarial Networks (GANs), Neural Networks Generator and Discriminator, and Variational Autoencoders (VAEs). Examples of generative AI include ChatGPT for text, DALL-E and Midjourney for images, Jukebox and Amper Music for audio, Runway and Synthesia for video, and GitHub Copilot for coding.
What is Machine Learning? [27:04]
Machine learning empowers computers to learn from data without explicit programming. It allows computers to improve their performance based on experience. Examples include Google Search, Facebook's friend suggestions and ad displays, and Netflix's movie recommendations.
What is AI Agent? [32:06]
An AI agent is a software program designed to understand its environment, make decisions, and perform actions. It uses technologies like machine learning and natural language processing. Examples include Alexa and self-driving cars. You can develop AI agents for your business, such as chatbots, but it requires coding skills or hiring a company that specializes in AI programs.
General Formula for Writing Prompts [36:11]
A general formula for writing prompts involves defining the role, task, context, constraints, and output style. The formula includes: Role (e.g., "Act as a blog writer"), Task (e.g., "Write"), Context (adding background or details), Constraints (style, tone, font), and Output Style (word count, look and feel).
Basic and Advanced Techniques in Prompt Engineering [45:41]
Basic techniques include zero-shot prompting (broad prompt without examples), few-shot prompting (providing a few examples), iterative prompting (refining results through multiple prompts), and structured prompting (following a specific order). Advanced techniques include chain of thoughts (COT) prompting (reasoning through a chain of thoughts), self-consistency prompting (asking the same question multiple times and choosing the most consistent answer), retrieval augmented generation (RAG) prompting (using external sources for information), and tree of thoughts (exploring different approaches to a question).
What are Tokens in Prompt Engineering? [53:09]
Tokens are pieces of text used by Large Language Models (LLMs) like ChatGPT. LLMs count tokens for both input and output to manage usage, especially in paid plans. Tokens help limit usage and determine costs and speeds in AI APIs.
Types of Prompts [1:02:18]
Different types of prompts are used for different purposes. AI and machine learning prompts include instructional, descriptive, few-shot, zero-shot, chain of thought, and role-based prompts. Creative writing prompts include scenario, character, dialogue, and first-line prompts. Visual prompts include art style, photography, and concept prompts. Marketing and branding prompts include ad copy, tagline, and social media prompts. Educational prompts include question, discussion, and reflection prompts.
Zero Shot Prompting [1:06:39]
Zero-shot prompting involves providing a task to a language model without any examples or specific instructions. This often results in vague or general outputs. It is useful for generating initial ideas.
One Shot Prompting [1:09:31]
One-shot prompting involves providing a single example to guide the language model. This provides more focused results compared to zero-shot prompting.
Few Shot Prompting [1:12:52]
Few-shot prompting involves providing several examples to the language model, leading to more accurate and structured outputs compared to zero-shot and one-shot prompting.
Chain of Thought Prompting [1:16:32]
Chain of Thought (COT) prompting involves providing a series of interconnected prompts to guide the AI in reasoning and providing detailed explanations. Instead of a direct question, the AI is prompted to think step-by-step, leading to more reliable and accurate answers.
Meta Prompting [1:22:23]
Meta-prompting is a technique that uses large language models to create or refine prompts. It involves either generating prompts from scratch or refining existing prompts to improve results.
Self Consistency Prompting [1:27:43]
Self-consistency prompting involves asking the AI the same question multiple times or in different ways and selecting the most consistent and accurate response. This technique enhances the reliability and accuracy of AI models.
Tree of Thoughts Prompting [1:31:22]
Tree of Thoughts (ToT) prompting is a technique used for complex problem-solving. It involves providing the AI with a method to think about a question in multiple ways, similar to a tree with different branches, to generate more thoughtful and reliable responses.
Levels, Techniques, and Purposes of Prompt Engineering [1:37:39]
Prompt engineering techniques vary in level, from basic to advanced, and serve different purposes. Basic techniques set the tone and add background information. Intermediate techniques teach with examples and use step-wise reasoning. Advanced techniques explore multiple solutions, react with reasoning and action, and use multi-version thinking. Meta-prompting involves chaining multi-step creative outputs and auto-optimization. Visual techniques include negative prompting to control unwanted elements.
Practical Use of Prompts for Text, Images, and Videos [1:44:00]
The course will now focus on practical applications of prompts for text, images, and videos. This includes writing scripts, emails, and blog content, generating images for social media, and creating videos.
How to Write a Perfect Prompt for Letter Writing [1:46:46]
To write a perfect prompt for letter writing, include the type of letter (formal or informal), the purpose of the letter, the tone (polite, emotional, professional, friendly), receiver details, sender details, key points, and the desired length.
How to Create a Resume Using AI [1:59:22]
To create a resume using AI, start by choosing a resume format (reverse chronological, functional, or combination). Include a strong resume header with your full name, job title, contact number, email ID, and links to your LinkedIn profile and portfolio. Write a powerful summary highlighting your key achievements and skills. List your technical and soft skills. Provide details of your work experience, including company name, designation, duration, and key achievements. Include your education details and certifications. Add optional sections like projects, languages, and hobbies. Use a prompt formula with inputs like name, job title, experience level, company name, skills, achievements, education, certifications, contact info, and tone preference.
How to Write a Blog Using AI [2:08:18]
To write a blog using AI, start by identifying your audience and goal. Validate the topic by researching keywords. Create a content brief with the title, target reader, call to action, key points, examples, and assets. Plan the outline with a hook, intro, H1 title, H2 sections, summary, and CTA. Draft the content using AI, add proof, and optimize for SEO. Edit and proofread the content, ensure a strong intro and CTA, and then publish and promote the blog.
How to Create a Website Using AI [2:29:45]
To create a website using AI, use website builders from trusted sources like GoDaddy and Hostinger. These platforms offer AI-driven tools within their domain and hosting services. Sign up for a free account, choose a website type (online store, professional website), and provide details about your business. The AI will generate a basic website structure that you can customize.
How to Generate Images Using AI [2:41:38]
To generate images using AI, provide detailed prompts specifying the desired elements, style, and composition. Use tools like ChatGPT to generate prompts for specific types of images, such as cinematic images.
How to Use Gemini 1.5 Pro for Various Tasks [2:54:31]
Gemini 1.5 Pro can be used for various tasks, including generating professional websites, creating AI images, generating social media posts, creating character designs, generating videos, generating speech, and creating storybooks. The pro version offers high-quality video clips, deep research features, and increased storage.
How to Summarize Videos and Generate Captions Using NoteGPT [4:08:46]
NoteGPT is an AI learning assistant that can summarize videos and generate captions. Sign up for a free account, paste the YouTube video link, and click "Summarize Now." The tool will generate a transcript and summary of the video.
How to Use RmakerAI for Image and Video Editing [4:15:06]
RmakerAI is an AI photo editing tool that offers features like image upscaling, background removal, photo enhancement, and video tools. Sign up for a free account to access 30 credits. Use the AI Photo Generator to create logos, avatars, and headshots. Enhance video quality with the video enhancer and generate videos from text or images.
How to Use Leonardo AI for Image Generation and Editing [4:31:09]
Leonardo AI is an AI tool for image generation and editing. It offers features like real-time canvas, image generation, motion creation, and canvas editing. Use the real-time canvas to draw and generate images in real-time. Use image creation to generate images from text prompts. Enhance images using the upscaler and edit images using the canvas editor.
