Who is Data Scientist?

He/she is responsible for collecting, analyzing and interpreting the results, through a large amount of data. This process is used to take an important decision for the business, which can affect the growth and help to face compititon in the market.

A data scientist analyzes data to extract actionable insight from it. More specifically, a data scientist:

Determines correct datasets and variables.

Identifies the most challenging data-analytics problems.

Collects large sets of data- structured and unstructured, from different sources.

Cleans and validates data ensuring accuracy, completeness, and uniformity.

Builds and applies models and algorithms to mine stores of big data.

Analyzes data to recognize patterns and trends.

Interprets data to find solutions.

Communicates findings to stakeholders using tools like visualization.

Join our WhatsApp channel to learn more: https://whatsapp.com/channel/0029Va8v3eo1NCrQfGMseL2D

𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀😍

Whether you’re a student, fresher, or professional looking to upskill — Microsoft has dropped a series of completely free courses to get you started.

Learn SQL ,Power BI & More In 2025 

𝗟𝗶𝗻𝗸:-👇

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𝟯 𝗙𝗿𝗲𝗲 𝗧𝗖𝗦 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗘𝘃𝗲𝗿𝘆 𝗙𝗿𝗲𝘀𝗵𝗲𝗿 𝗠𝘂𝘀𝘁 𝗧𝗮𝗸𝗲 𝘁𝗼 𝗚𝗲𝘁 𝗝𝗼𝗯-𝗥𝗲𝗮𝗱𝘆😍

🎯 If You’re a Fresher, These TCS Courses Are a Must-Do📄✔️

Stepping into the job market can be overwhelming—but what if you had certified, expert-backed training that actually prepares you?👨‍🎓✨️

𝐋𝐢𝐧𝐤👇:-

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Don’t wait. Get certified, get confident, and get closer to landing your first job✅️

𝗙𝗿𝗲𝗲 𝗖𝗼𝘂𝗿𝘀𝗲 𝘄𝗶𝘁𝗵 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗲 𝗯𝘆 𝗚𝗼𝗼𝗴𝗹𝗲 – 𝗟𝗲𝗮𝗿𝗻 𝗣𝘆𝘁𝗵𝗼𝗻 𝗳𝗼𝗿 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀😍

If you’re starting your journey into data analytics, Python is the first skill you need to master👨‍🎓

A free, beginner-friendly course by Google on Kaggle, designed to take you from zero to data-ready with hands-on coding practice👨‍💻📝

𝐋𝐢𝐧𝐤👇:-

https://pdlink.in/4k24zGl

Just start coding right in your browser✅️

You can use ChatGPT to make money online.

Here are 10 prompts by ChatGPT

1. Develop Email Newsletters:

Make interesting email newsletters to keep audience updated and engaged.

Prompt: "I run a local community news website. Can you help me create a weekly email newsletter that highlights key local events, stories, and updates in a compelling way?"

2. Create Online Course Material:

Make detailed and educational online course content.

Prompt: "I'm creating an online course about basic programming for beginners. Can you help me generate a syllabus and detailed lesson plans that cover fundamental concepts in an easy-to-understand manner?"

Read more......

5 Powerful ChatGPT prompts for customising resume:
____

Prompt 1: Analysis of the Job Description

Analyze the below job description carefully and let me know 5 top skills required to be a perfect candidate for this job description (JD):

”Paste JD”

Prompt 2: Create a Career Summary:

Please create a summary of my resume. Include points around [keywords]. Also, include 5-6 key highlights in bullet points in the summary

Here is the resume text in quotes: “Paste Resume text”

Here is the Job Description in quotes: “Paste Job Description”

Prompt 3: Create Resume pointers from your work Summary:

I am applying for a [Type Role] role. Act as a resume writer and create 4 resume bullet points from the below work experience mentioned in the quotes. Start the bullet points with action verbs and write them in crisp language. Add numbers to show impact. Add a dummy number, if the exact data is not available and I will input the correct data later.

Here is the work summary text in quotes: “Paste text”

Prompt 4: Refine a resume pointer

I am applying for a [Type Role] role. Act as a resume writer and create 5 different versions of the below-given resume bullet point.

Length should be less than 20 words.
Each point should start with an action verb.
It should follow ‘𝘈𝘤𝘤𝘰𝘮𝘱𝘭𝘪𝘴𝘩𝘦𝘥 [𝘟] 𝘢𝘴 𝘮𝘦𝘢𝘴𝘶𝘳𝘦𝘥 𝘣𝘺 [𝘠], 𝘣𝘺 𝘥𝘰𝘪𝘯𝘨 [𝘡].’ Framework for structuring the bullet point.

👉WhatsApp Channel: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226

👉Telegram Link: https://t.me/addlist/ID95piZJZa0wYzk5

All the best 👍👍

𝟱 𝗙𝗿𝗲𝗲 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗬𝗼𝘂 𝗖𝗮𝗻’𝘁 𝗠𝗶𝘀𝘀😍

Microsoft Learn is offering 5 must-do courses for aspiring data scientists, absolutely free🔥📊

These self-paced learning modules are designed by industry experts and cover everything from Python and ML to Microsoft Fabric and Azure🎯

𝐋𝐢𝐧𝐤👇:-

https://pdlink.in/4iSWjaP

Job-ready content that gets you results✅️

AI/ML (Daily Schedule) 👨🏻‍💻

Morning:
- 9:00 AM - 10:30 AM: ML Algorithms Practice
- 10:30 AM - 11:00 AM: Break
- 11:00 AM - 12:30 PM: AI/ML Theory Study

Lunch:
- 12:30 PM - 1:30 PM: Lunch and Rest

Afternoon:
- 1:30 PM - 3:00 PM: Project Development
- 3:00 PM - 3:30 PM: Break
- 3:30 PM - 5:00 PM: Model Training/Testing

Evening:
- 5:00 PM - 6:00 PM: Review and Debug
- 6:00 PM - 7:00 PM: Dinner and Rest

Late Evening:
- 7:00 PM - 8:00 PM: Research and Reading
- 8:00 PM - 9:00 PM: Reflect and Plan

Best Data Science & Machine Learning Resources: https://topmate.io/coding/914624

ENJOY LEARNING 👍👍

𝗕𝗼𝗼𝘀𝘁 𝗬𝗼𝘂𝗿 𝗦𝗸𝗶𝗹𝗹𝘀 𝘄𝗶𝘁𝗵 𝗧𝗵𝗲𝘀𝗲 𝗙𝗿𝗲𝗲 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀😍

Ready to take your career to the next level?📊📌

These free certification courses offer a golden opportunity to build expertise in tech, programming, AI, and more—all for free!🔥💻

𝐋𝐢𝐧𝐤👇:-

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These courses are your stepping stones to success✅️

𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗩𝗶𝗿𝘁𝘂𝗮𝗹 𝗜𝗻𝘁𝗲𝗿𝗻𝘀𝗵𝗶𝗽 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝘀 𝗜𝗻 𝗧𝗼𝗽 𝗖𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀😍

1️⃣ BCG Data Science & Analytics Virtual Experience
2️⃣ TATA Data Visualization Internship
3️⃣ Accenture Data Analytics Virtual Internship

𝐋𝐢𝐧𝐤👇:-

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Enroll for FREE & Get Certified 🎓

🔴 How to MASTER a programming language using ChatGPT: 📌

1. Can you provide some tips and best practices for writing clean and efficient code in [lang]?

2. What are some commonly asked interview questions about [lang]?

3. What are the advanced topics to learn in [lang]? Explain them to me with code examples.

4. Give me some practice questions along with solutions for [concept] in [lang].

5. What are some common mistakes that people make in [lang]?

6. Can you provide some tips and best practices for writing clean and efficient code in [lang]?

7. How can I optimize the performance of my code in [lang]?

8. What are some coding exercises or mini-projects I can do regularly to reinforce my understanding and application of [lang] concepts?

9. Are there any specific tools or frameworks that are commonly used in [lang]? How can I learn and utilize them effectively?

10. What are the debugging techniques and tools available in [lang] to help troubleshoot and fix code issues?

11. Are there any coding conventions or style guidelines that I should follow when writing code in [lang]?

12. How can I effectively collaborate with other developers in [lang] on a project?

13. What are some common data structures and algorithms that I should be familiar with in [lang]?

Join for more: https://t.me/AI_Best_Tools

𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝟭𝟬𝟬% 𝗙𝗿𝗲𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗳𝗼𝗿 𝗔𝘇𝘂𝗿𝗲, 𝗔𝗜, 𝗖𝘆𝗯𝗲𝗿𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆 & 𝗠𝗼𝗿𝗲😍

Want to upskill in Azure, AI, Cybersecurity, or App Development—without spending a single rupee?👨‍💻🎯

Enter Microsoft Learn — a 100% free platform that offers expert-led learning paths to help you grow📊📌

𝐋𝐢𝐧𝐤👇:-

https://pdlink.in/4k6lA2b

Enjoy Learning ✅️

Try this powerful AI prompt...

It can create Instagram captions that people actually read...

And with IG Captions being one of the most underrated elements for increasing:

- Reach (through IG SEO)
- Engagement (by providing context)
- Sales (by building trust + automation)

This prompt can change the game for you on Instagram...

And it works on ChatGPT, Gemini, Copilot, Claude...
(and any other LLM)

Just copy and paste it and enjoy the results...

1️⃣ First, we set the persona 👇

1️⃣ The persona is:

"Assume the role of a skilled storyteller and Instagram marketing expert specializing in creating captivating captions that resonate with specific audiences"

2️⃣ Then we state our expectations:

"Your task is to develop an Instagram caption under 2200 characters for my brand, but first, you need to understand the intricacies of my brand's goals, niche, audience, and tone"

3️⃣ Afterwards, we ask it to customise the outcome by 👇

3️⃣Instructing it to ask us 10 questions + restricting data hallucination:

"Please begin by asking me 10 questions to gather essential information, providing multiple choice answers, and remembering my responses. Don’t hallucinate"

4️⃣We are almost there, next we 👇

4️⃣Teach the bot what a good caption looks like:

"After receiving the answers, proceed to create a caption that:

- Starts with an attention-grabbing hook.
- Utilizes storytelling to connect with the audience.
- Seamlessly highlights the featured product/service.
- Employs emotive language for greater impact.
- Concludes with a clear and compelling call-to-action"

5️⃣And lastly we👇

5️⃣Summarise everything + set a "firing" rule: |

"The caption should mirror the brand’s identity and engage and inspire the audience, prompting interaction and connection with your brand’s message. You will be fired if you supply a generic caption"

𝗟𝗲𝗮𝗿𝗻 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗳𝗿𝗼𝗺 𝗚𝗼𝗼𝗴𝗹𝗲 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝘀 — 𝗙𝗼𝗿 𝗙𝗿𝗲𝗲!😍

Want to break into machine learning but not sure where to start?💻

Google’s Machine Learning Crash Course is the perfect launchpad—absolutely free, beginner-friendly, and created by the engineers behind the tools.👨‍💻📌

𝐋𝐢𝐧𝐤👇:-

https://pdlink.in/4jEiJOe

All The Best 🎊

Data Analyst Vs Data Scientist

**Data Analyst******
Focus: Data analysts primarily work with existing data sets to extract meaningful insights and draw conclusions.
Skills: They possess strong skills in data cleaning, data visualization, and statistical analysis. They are proficient in tools like Excel, SQL, and data visualization software.
Responsibilities: Data analysts are responsible for gathering, organizing, and cleaning data. They perform exploratory data analysis, generate reports, and create visualizations to communicate findings to stakeholders.
Goals: They aim to identify trends, patterns, and correlations within the data, and provide actionable recommendations based on their analysis.
Domain Expertise: They may specialize in specific business domains and apply their analytical skills to solve domain-specific problems.

***Data Scientist:***
Focus: Data scientists are involved in both analyzing existing data and developing predictive models or algorithms to solve complex problems.
Skills: They have a strong foundation in mathematics, statistics, programming, and machine learning. They are proficient in languages like Python or R and have knowledge of advanced statistical techniques.
Responsibilities: Data scientists collect and analyze data, develop and implement predictive models and algorithms, and apply machine learning techniques to extract insights and make predictions. They also work on data preprocessing, feature engineering, and model evaluation.
Goals: They aim to uncover hidden patterns, create predictive models, and make data-driven decisions. They often deal with large volumes of unstructured or complex data.
Domain Expertise: They possess a deep understanding of statistical and machine learning concepts and can apply their expertise across various domains.
In summary, data analysts focus on analyzing and interpreting existing data sets to generate insights, while data scientists have a broader skill set and are involved in developing models and algorithms to solve complex problems. Data scientists require a deeper knowledge of mathematics, statistics, and programming, including machine learning techniques.

𝗔𝗱𝘃𝗮𝗻𝗰𝗲 𝗬𝗼𝘂𝗿 𝗖𝗮𝗿𝗲𝗲𝗿 𝗶𝗻 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝘄𝗶𝘁𝗵 𝗧𝗵𝗲𝘀𝗲 𝗧𝗼𝗽 𝗖𝗼𝘂𝗿𝘀𝗲𝘀😍

✅ Microsoft Power BI Data Analyst Professional Certificate
✅ Meta Data Analyst Professional Certificate
✅ IBM Data Analyst Capstone Project

𝐋𝐢𝐧𝐤👇:-

https://pdlink.in/49X5JPB

💡 𝗧𝗶𝗽 𝘁𝗼 𝗔𝗰𝗰𝗲𝘀𝘀 𝗧𝗵𝗲𝘀𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗳𝗼𝗿 𝗙𝗿𝗲𝗲 (𝗖𝗵𝗲𝗰𝗸 𝗶𝗻 𝗪𝗲𝗯𝘀𝗶𝘁𝗲)📌