Master Generative AI with expert training
Generative AI training for business professionals & entrepreneurs
Free Trial
15-days refund
Free tutor swap
No cancel fee
Summary
Podcast
null
vasundhra taught 6 days ago
The Student and Tutor engaged in a comprehensive C++ programming session, covering conditional statements, boolean logic, and character operations. They practiced detecting number ranges using `if-else` structures, implemented `switch` statements, and worked with functions from the `cctype` library for string manipulation. The session culminated in a coding lab where the Student wrote a program to find the smallest of three input integers, with plans to start the next section in the following session.
Conditional `if-else if-else` for Range Detection
Switch Statements for Multibranch Control
Boolean Data Types and Logical Operators
Character Operations with the `<cctype>` Library
Faria taught 22 days ago
The student and tutor worked through challenges related to Python's object-oriented programming, focusing on inheritance and the diamond problem. They practiced modifying code to alter method resolution order and then built a "Superhero Game" by creating child classes that inherited from parent classes and overrode methods.
Object-Oriented Programming (OOP) Inheritance
Method Resolution Order (MRO)
The Diamond Problem in Inheritance
Super() Function in Python
Instance Attributes vs. Class Attributes
Avni taught 29 days ago
The tutor and student focused on practical digital marketing skills, specifically creating visually appealing social media posts for an online business using Canva and AI tools. They practiced image editing, template selection, and content integration, with plans to develop custom posts and explore further training on business strategy.
Facebook Business Page Setup
Social Media Posting Workflow
Image Editing: Background Removal
Content Creation with Canva
Avni taught about 2 months ago
The Student and Tutor reviewed stack-related homework, focusing on finding the Kth element in a stack and the importance of copying the stack to maintain data integrity. The session then introduced queues, discussing their First-In, First-Out (FIFO) principle, core operations, and the difference between using inbuilt C++ libraries versus implementing custom queue functionalities. They practiced finding the second highest element in a queue, with the Tutor demonstrating an optimized single-loop solution, and discussed assigned queue-related homework questions.
Stacks: Efficient Kᵗʰ Element Retrieval
Introduction to Queues (FIFO)
C++ `std::queue` vs. Custom Queue Implementation
Optimized Second Highest Element in a Queue
vasundhra taught 2 months ago
The Student and Tutor reviewed key concepts in Cryptography, focusing on hashing functions like MD5 for data integrity and secure password storage. Subsequently, they transitioned to Java programming, covering user-defined methods, parameters (including multiple and array parameters), and various array operations. The Student practiced defining methods, passing arguments, and solving several coding exercises involving array traversal, value finding, and element updates, with plans to complete the remaining parts of the current exercise in the next session.
Hashing for Data Integrity
Cryptographic Hashing & Password Security
User-Defined Methods in Java
Parameter Passing: Primitive vs. Array Types
Array Traversal and Manipulation
Neha taught 3 months ago
The Student and Tutor reviewed core Python programming concepts, specifically focusing on functions and various string operations. They practiced defining and calling functions with different argument types and explored fundamental string manipulations, including slicing, concatenation, and checking for immutability and escape characters. The session concluded with the Student needing to review modules and dictionaries for an upcoming quiz, with a follow-up session scheduled.
Iterating Strings with Loops and Conditionals
String Immutability and Escape Characters
String Basics: Definition
Concatenation
and Formatting
Python Functions: Definition
Arguments
and Return Values
Essential generative AI capabilities from certified expert trainers
Discover other AI training for specialized tools and applications
Master specific AI tools and enterprise workflows
What Is Gen AI and How Does It Work?
At its core, Generative AI refers to deep-learning models that can generate novel content, including text, images, audio, and code. The most common type of Generative AI is built on Large Language Models (LLMs), which are trained on vast amounts of text and data from the internet.
The process is conceptually simple: the model learns the patterns, structures, grammar, and relationships within its training data. When given a prompt (a user's instruction), it uses this learned knowledge to predict the next most logical word, pixel, or note in a sequence. By repeating this process millions of times per second, it can construct entire sentences, paragraphs, images, and more that are coherent, contextually relevant, and often indistinguishable from human-created content. This core ability to predict and create is what makes it a "generative" technology.
Gen AI Training
This comprehensive course is designed to equip you with the essential skills to effectively leverage Generative AI. The curriculum is structured into four core modules, guiding you from fundamental principles to advanced, responsible application in your professional life.
Module 1: Foundations of Generative AI
This introductory module provides the essential background knowledge needed to understand the technology. Upon completion, you will be able to differentiate between various AI models and understand the key concepts that power them.
Key Topics Covered:
- The distinction between traditional AI and Generative AI.
- An introduction to Large Language Models (LLMs), neural networks, and key terminology (tokens, parameters).
- A comprehensive overview of the major AI platforms (ChatGPT, Gemini, Claude) and their unique strengths.
- An introduction to specialised models for image generation (Midjourney, DALL-E).
Module 2: The Core Skill of Prompt Engineering
This practical module is focused on developing the most critical skill for using Generative AI: prompt engineering. You will learn to communicate your intent to the AI with precision to achieve high-quality, relevant results.
Key Topics Covered:
- The principles of writing clear, specific, and context-rich prompts.
- Advanced techniques, including assigning a "persona," using "few-shot" examples, and structuring complex, multi-step instructions.
- The art of iterative prompting: how to refine and guide the AI through conversational follow-ups.
Module 3: Strategic Application in the Real World
This module bridges the gap between theory and practice, focusing on integrating Generative AI into specific professional workflows to drive productivity and innovation.
Key Topics Covered:
- Workflow Integration: Tailored strategies for using AI in marketing, software development, data analysis, and business administration.
- Task-Specific Tool Selection: Learn how to choose the right AI tool for the job, whether you need a text-generator, an image creator, or a multimodal analysis engine.
- Automating Routine Tasks: Practical exercises in using AI to summarise documents, draft communications, and generate creative ideas.
Module 4: Responsible AI Practices and Ethical Considerations
In this final, crucial module, students will learn to use Generative AI as a critical and responsible tool. The focus is on understanding the limitations and ethical dimensions of the technology.
Key Topics Covered:
- Identifying and Mitigating "Hallucinations": Learn the importance of fact-checking and verifying AI-generated information.
- Understanding and Addressing Bias: Recognise how biases in training data can be reflected in AI outputs.
- Ethical Guidelines: Best practices for using AI in a way that is transparent, fair, and respects intellectual property.
Meet the New Generation of AI-Powered Users
Generative AI is not a tool for a single type of person; it's a versatile platform adopted by a diverse range of users. Here are some of the key personas emerging in this new landscape:
The Strategic Professional: In the world of business, this user views AI as a productivity engine. They leverage it to automate the mundane drafting of reports, summarising long email chains, and analysing spreadsheets in order to accelerate their workflow. By offloading these repetitive tasks, they free up valuable mental energy to focus on what truly matters: high-level strategy, critical thinking, and driving business growth.
The Lifelong Learner: For students and educators, AI is the ultimate knowledge companion. It acts as a tireless research assistant that can synthesise complex academic papers in seconds, and a 24/7 personal tutor that can break down difficult concepts into simple, understandable terms. Educators also use it as a teaching assistant, helping them create engaging lesson plans and educational materials.
The Creative Visionary: This user be they an artist, a writer, or a developer, sees AI as a creative co-pilot. It's a partner in the brainstorming process, helping to overcome creative blocks by suggesting new ideas. It can generate first drafts of articles, produce stunning concept art from a simple description, or write and debug lines of code, acting as a powerful accelerator for turning imagination into reality.
The Everyday Optimiser: This person uses Generative AI to streamline their personal life. They are the ultimate life-hackers, using AI to draft the perfect email to a landlord, plan a detailed week-long vacation itinerary, create a personalised workout routine, or even just come up with a witty caption for a social media post. For them, AI is a practical tool for making daily life easier and more efficient.
