Use Chat GPT to prepare for your next Interview

This could be the most helpful thing for people aspiring for new jobs.

A few prompts that can help you here are:

💡Prompt 1: Here is a Job description of a job I am looking to apply for. Can you tell me what skills and questions should I prepare for? {Paste JD}

💡Prompt 2: Here is my resume. Can you tell me what optimization I can do to make it more likely to get selected for this interview? {Paste Resume in text}

💡Prompt 3: Act as an Interviewer for the role of a {product manager} at {Company}. Ask me 5 questions one by one, wait for my response, and then tell me how I did. You should give feedback in the following format: What was good, where are the gaps, and how to address the gaps?

💡Prompt 4: I am interviewing for this job given in the JD. Can you help me understand the company, its role, its products, main competitors, and challenges for the company?

💡Prompt 5: What are the few questions I should ask at the end of the interview which can help me learn about the culture of the company?

Free book to master ChatGPT: https://t.me/InterviewBooks/166

ENJOY LEARNING 👍👍

🤖 7 Powerful ChatGPT Prompts
to Create SEO Content Faster...

Which AI is better — with a wrapper or without?

I liked a slide from the recent presentation Sequoia Capital AI Ascent 2025.

Big vendors after the launch of ChatGPT insisted that niche and industrial startups consuming AGI intelligence are unpromising.

They disdainfully called them AI wrappers, believing that they have no protection against competitors.

A couple of years later, we observe record growth precisely in such companies as Cursor ($300 million ARR), Loveable, Windsurf (bought by OpenAI for $3 billion), and thousands of new industrial startups — in finance, insurance, e-commerce, legal, accounting, healthcare, and other sectors.

Meanwhile, AI tokens are becoming the fastest depreciating technology and currency in history.

According to Sam Altman himself, over time the cost of AI will equal the cost of energy.

Giants have started giving access to their most powerful AI models to seize leadership in the new technological era.

I have already written about a unique market moment: when, being an expert in any subject area, you combine your knowledge with the growing capabilities of AI — and get a tool that solves real human problems for which clients are ready to pay immediately.

Now these very AI wrappers have turned into serious businesses.

The obvious challenge for entrepreneurs is that AI skills and specialists are increasing in value much faster than other segments of the IT market.

Startups and mature companies with subject matter experts already face difficulties attracting strong AI engineers, but at the same time, according to the results of the first internal hackathons, I see a rapid increase in the number of those who caught the trend and felt in AI a breath of fresh air in the enterprise world.

In the coming years, young founders and enthusiasts who live by technology, see trends ahead, and tirelessly experiment by creating new products will win rapidly.

Time to act!

𝗧𝗼𝗽 𝗖𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝗛𝗶𝗿𝗶𝗻𝗴 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝘁𝘀😍

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Artificial Intelligence (AI) is the simulation of human intelligence in machines that are designed to think, learn, and make decisions. From virtual assistants to self-driving cars, AI is transforming how we interact with technology.

Hers is the brief A-Z overview of the terms used in Artificial Intelligence World

A - Algorithm: A set of rules or instructions that an AI system follows to solve problems or make decisions.

B - Bias: Prejudice in AI systems due to skewed training data, leading to unfair outcomes.

C - Chatbot: AI software that can hold conversations with users via text or voice.

D - Deep Learning: A type of machine learning using layered neural networks to analyze data and make decisions.

E - Expert System: An AI that replicates the decision-making ability of a human expert in a specific domain.

F - Fine-Tuning: The process of refining a pre-trained model on a specific task or dataset.

G - Generative AI: AI that can create new content like text, images, audio, or code.

H - Heuristic: A rule-of-thumb or shortcut used by AI to make decisions efficiently.

I - Image Recognition: The ability of AI to detect and classify objects or features in an image.

J - Jupyter Notebook: A tool widely used in AI for interactive coding, data visualization, and documentation.

K - Knowledge Representation: How AI systems store, organize, and use information for reasoning.

L - LLM (Large Language Model): An AI trained on large text datasets to understand and generate human language (e.g., GPT-4).

M - Machine Learning: A branch of AI where systems learn from data instead of being explicitly programmed.

N - NLP (Natural Language Processing): AI's ability to understand, interpret, and generate human language.

O - Overfitting: When a model performs well on training data but poorly on unseen data due to memorizing instead of generalizing.

P - Prompt Engineering: Crafting effective inputs to steer generative AI toward desired responses.

Q - Q-Learning: A reinforcement learning algorithm that helps agents learn the best actions to take.

R - Reinforcement Learning: A type of learning where AI agents learn by interacting with environments and receiving rewards.

S - Supervised Learning: Machine learning where models are trained on labeled datasets.

T - Transformer: A neural network architecture powering models like GPT and BERT, crucial in NLP tasks.

U - Unsupervised Learning: A method where AI finds patterns in data without labeled outcomes.

V - Vision (Computer Vision): The field of AI that enables machines to interpret and process visual data.

W - Weak AI: AI designed to handle narrow tasks without consciousness or general intelligence.

X - Explainable AI (XAI): Techniques that make AI decision-making transparent and understandable to humans.

Y - YOLO (You Only Look Once): A popular real-time object detection algorithm in computer vision.

Z - Zero-shot Learning: The ability of AI to perform tasks it hasn’t been explicitly trained on.

Credits: https://whatsapp.com/channel/0029Va4QUHa6rsQjhITHK82y

𝟰 𝗙𝗿𝗲𝗲 𝗣𝘆𝘁𝗵𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝘁𝗼 𝗕𝗼𝗼𝘀𝘁 𝗬𝗼𝘂𝗿 𝗥𝗲𝘀𝘂𝗺𝗲 𝗶𝗻 𝟮𝟬𝟮𝟱😍

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Enjoy Learning ✅️

ChatGPT can help you land your dream job twice as fast. Here are 8 powerful ChatGPT prompts will 10X your interview chances.

Free book to master ChatGPT: https://t.me/InterviewBooks/166

1. Customizing Your Resume ChatGPT prompt: "Can you make changes to my resume to fit the [Job Title] role at [Company]? Here's the job description: [Paste Job Description], and resume: [Paste Resume]."

2. Creating a Professional Summary ChatGPT prompt: "Using my resume, can you create a professional summary for me aligned to this [Job Title]." [Paste Resume]

3. Understanding Job Descriptions ChatGPT prompt: "What are the main responsibilities for this job? Please list the top three responsibilities required for [Job Title]." [Paste Job Description]

4. Improving Your Resume Bullets ChatGPT prompt: "Please rewrite this bullet point from my resume using clear and impactful language while highlighting my accomplishments. [Paste Resume]"

5. Writing a LinkedIn Summary ChatGPT prompt: "Can you write a summary for my LinkedIn profile using my resume [Paste Resume]?"

6. Job Applications with ChatGPT ChatGPT prompt: "Can you identify my [Skills] experience from my resume [Paste Resume]? Please describe my specific [Skills] experience in conversational, clear language as if you were me."

7. Crafting Your Cover Letter ChatGPT prompt: "Can you write a personalized cover letter for the [Job Title] position at [Company]? Here's the job description: [Paste Job Description], and my current resume: [Paste Resume]."

8. Preparing for Interviews ChatGPT prompt: "What skills and experiences should I emphasize during an interview for the [Job Title] role in [Specific Industry]?"

ENJOY LEARNING 👍👍

𝗠𝗮𝘀𝘁𝗲𝗿 𝟲 𝗜𝗻-𝗗𝗲𝗺𝗮𝗻𝗱 𝗦𝗸𝗶𝗹𝗹𝘀 𝗳𝗼𝗿 𝗙𝗥𝗘𝗘!😍

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𝗧𝗵𝗲 𝗕𝗲𝘀𝘁 𝗙𝗿𝗲𝗲 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗖𝗵𝗲𝗮𝘁 𝗦𝗵𝗲𝗲𝘁 𝗼𝗻 𝗚𝗶𝘁𝗛𝘂𝗯 𝗘𝘃𝗲𝗿𝘆 𝗕𝗲𝗴𝗶𝗻𝗻𝗲𝗿 𝗦𝗵𝗼𝘂𝗹𝗱 𝗕𝗼𝗼𝗸𝗺𝗮𝗿𝗸😍

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Must-have resource for students and professionals✅️

This is a class from Harvard University:

"Introduction to Data Science with Python."

It's free. You should be familiar with Python to take this course.

The course is for beginners. It's for those who want to build a fundamental understanding of machine learning and artificial intelligence.

It covers some of these topics:

• Generalization and overfitting
• Model building, regularization, and evaluation
• Linear and logistic regression models
• k-Nearest Neighbor
• Scikit-Learn, NumPy, Pandas, and Matplotlib

Link: https://pll.harvard.edu/course/introduction-data-science-python