📌Natwest Group is hiring for Data & Analytics Analyst
Experience: 0 - 2 year's
Expected Salary: 12 - 20 LPA
Apply here: https://jobs.natwestgroup.com/jobs/15983178-data-and-analytics-analyst-da?tm_job=R-00255555&tm_event=view&tm_company=861&bid=56

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

👉 Telegram Channel: https://t.me/addlist/4q2PYC0pH_VjZDk5

All the best! 👍👍

📌Beckman Coulter Diagnostics is hiring for Data Science Intern
Experience: 0 - 2 year's
Apply here: https://jobs.danaher.com/global/en/job/DANAGLOBALR1292567EXTERNALENGLOBAL/Data-Science-Intern

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

👉 Telegram Channel: https://t.me/addlist/4q2PYC0pH_VjZDk5

All the best! 👍👍

𝟲 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗙𝗿𝗼𝗺 𝗧𝗼𝗽 𝗢𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝘀 😍

A power-packed selection of 100% free, certified courses from top institutions:

- Data Analytics – Cisco
- Digital Marketing – Google
- Python for AI – IBM/edX
- SQL & Databases – Stanford
- Generative AI – Google Cloud
- Machine Learning – Harvard

𝗘𝗻𝗿𝗼𝗹𝗹 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘👇:- 
 
https://pdlink.in/3FcwrZK
 
Master in‑demand tech skills with these 6 certified, top-tier free courses

🚀 𝟳 𝗙𝗿𝗲𝗲 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 + 𝗟𝗶𝗻𝗸𝗲𝗱𝗜𝗻 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝘁𝗼 𝗕𝗼𝗼𝘀𝘁 𝗬𝗼𝘂𝗿 𝗖𝗮𝗿𝗲𝗲𝗿 𝗶𝗻 𝟮𝟬𝟮𝟱 😍

Gain globally recognized skills with Microsoft x LinkedIn Career Essentials – completely FREE!

🎯 Top Certifications:
🔹 Generative AI
🔹 Data Analysis
🔹 Software Development
🔹 Project Management
🔹 Business Analysis
🔹 System Administration
🔹 Administrative Assistance

📚 100% Free | Self-Paced | Industry-Aligned

𝗘𝗻𝗿𝗼𝗹𝗹 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘👇:- 
 
https://pdlink.in/46TZP2h
 
💼 Perfect for students, freshers & working professionals

𝗪𝗮𝗻𝘁 𝘁𝗼 𝗠𝗮𝘀𝘁𝗲𝗿 𝗧𝗲𝗰𝗵 𝗦𝗸𝗶𝗹𝗹𝘀 𝗧𝗵𝗮𝘁 𝗖𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝗔𝗿𝗲 𝗛𝗶𝗿𝗶𝗻𝗴 𝗙𝗼𝗿?😍

If you’re looking to land a job in tech or simply want to upskill without spending money, this is your golden chance✨️📌

We’ve handpicked 5 YouTube channels that teach 5 in-demand tech skills for FREE. These skills are widely sought after by employers in 2025 — from startups to top MNCs🧑‍💻

𝐋𝐢𝐧𝐤👇:-

https://pdlink.in/46n3hCs

Here’s your roadmap — pick one, stay consistent, and grow daily✅️

Swiggy is hiring Data Scientist 🚀

Experience : 0-3 Years
Location : Bangalore

Apply link : https://careers.swiggy.com/#/careers?src=linkedin&p=eyJwYWdlVHlwZSI6ImpkIiwiY3ZTb3VyY2UiOiJsaW5rZWRpbiIsInJlcUlkIjoyMTA3MSwicmVxdWVzdGVyIjp7ImlkIjoibGlua2VkaW4iLCJjb2RlIjpudWxsLCJuYW1lIjoiIn19&reqid=21071

Dell Technologies is hiring!
Position: Data Science
Qualifications: Bachelor’s/ Master's Degree
Salary: 7 - 19 LPA (Expected)
Experience: Experienced
Location: Bangalore, India

📌Apply Now: https://jobs.dell.com/en/job/bengaluru/advisor-data-science-i7/375/84046538496

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

👉 Telegram Channel: https://t.me/addlist/4q2PYC0pH_VjZDk5

All the best! 👍👍

𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝘁 𝗝𝗼𝗯𝘀 𝗜𝗻 𝗧𝗼𝗽 𝗖𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 😍

𝗔𝗽𝗽𝗹𝘆 𝗟𝗶𝗻𝗸𝘀:-👇

Amazon : http://pdlink.in/3TRzydp

Ericsson : http://pdlink.in/4o5eH3U

Stryker : http://pdlink.in/3GXkqIz

Salesforce : http://pdlink.in/46qEGfY

Phenom : http://pdlink.in/3GFqsO1

Magna : http://pdlink.in/4o8rVgE

Apply before the link expires 💫

hiring freshers who are enthusiastic, quick learners, and ready to work on real-world AI/ML projects.
🔍 Role: Python & AI/ML Developer (Fresher)
📍 Location: Gurugram
🕐 Experience: 0–1 year
🧠 Skills: Python, Machine Learning Basics, Pandas, NumPy, Scikit-learn, Data Analysis
What You’ll Do:
✅ Assist in building ML models and data pipelines
✅ Collaborate with our AI/Tech team on live projects
✅ Learn and grow with guidance from experienced mentors
✅ Contribute to innovation and development of smart solutions

💼 What We Offer:
Real-time experience with AI/ML applications
Flexible work environment
Strong mentorship and training
Certificate of experience/completion
📩 Interested?
Send your resume to hr@turningcloud.com with the subject “Application – Python & AI/ML Developer (Fresher)”

𝗦𝘁𝗶𝗹𝗹 𝗙𝗮𝗶𝗹𝗶𝗻𝗴 𝗧𝗲𝗰𝗵 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄𝘀? 𝗧𝗵𝗲𝘀𝗲 𝟯 𝗙𝗿𝗲𝗲 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 𝗖𝗼𝘂𝗹𝗱 𝗙𝗶𝗻𝗮𝗹𝗹𝘆 𝗖𝗵𝗮𝗻𝗴𝗲 𝗧𝗵𝗮𝘁😍

You’ve spent hours solving LeetCode problems. You’ve gone through entire DSA playlists🗣✨️

The internet is filled with confusing roadmaps and endless practice sets. But what you need is clarity, structure, and confidence. That’s exactly what these 3 high-impact, free YouTube videos give you.👨‍💻📌

𝐋𝐢𝐧𝐤👇:-

https://pdlink.in/4feEnaA

This is your new cheat code✅️

Want to make a transition to a career in data?

Here is a 7-step plan for each data role

Data Scientist

Statistics and Math: Advanced statistics, linear algebra, calculus.
Machine Learning: Supervised and unsupervised learning algorithms.
xData Wrangling: Cleaning and transforming datasets.
Big Data: Hadoop, Spark, SQL/NoSQL databases.
Data Visualization: Matplotlib, Seaborn, D3.js.
Domain Knowledge: Industry-specific data science applications.

Data Analyst

Data Visualization: Tableau, Power BI, Excel for visualizations.
SQL: Querying and managing databases.
Statistics: Basic statistical analysis and probability.
Excel: Data manipulation and analysis.
Python/R: Programming for data analysis.
Data Cleaning: Techniques for data preprocessing.
Business Acumen: Understanding business context for insights.

Data Engineer

SQL/NoSQL Databases: MySQL, PostgreSQL, MongoDB, Cassandra.
ETL Tools: Apache NiFi, Talend, Informatica.
Big Data: Hadoop, Spark, Kafka.
Programming: Python, Java, Scala.
Data Warehousing: Redshift, BigQuery, Snowflake.
Cloud Platforms: AWS, GCP, Azure.
Data Modeling: Designing and implementing data models.

#data

🎓𝟱 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗧𝗼 𝗕𝗼𝗼𝘀𝘁 𝗬𝗼𝘂𝗿 𝗧𝗲𝗰𝗵 𝗖𝗮𝗿𝗲𝗲𝗿! 🚀

Upgrade your skills and earn industry-recognized certificates — 100% FREE!

✅ Big Data Analytics – https://pdlink.in/4nzRoza

✅ AI & ML – https://pdlink.in/401SWry

✅ Cloud Computing – https://pdlink.in/3U2sMkR

✅ Cyber Security – https://pdlink.in/4nzQaDQ

✅ Other Tech Courses – https://pdlink.in/4lIN673

🎯 Enroll Now & Get Certified for FREE

Micron Technology is hiring!
Position: Associate Engineer/ Engineer Data Science
Qualifications: Bachelor’s/ Master’s Degree
Salary: 10 16 LPA (Expected)
Experience: Freshers/ Experienced
Location: Hyderabad, India

📌Apply Now: https://micron.eightfold.ai/careers/job/30420709?domain=micron.com&hl=en

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

👉 Telegram Channel: https://t.me/addlist/4q2PYC0pH_VjZDk5

All the best! 👍👍

𝟲 𝗙𝗿𝗲𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝘁𝗼 𝗟𝗲𝗮𝗿𝗻 𝘁𝗵𝗲 𝗠𝗼𝘀𝘁 𝗜𝗻-𝗗𝗲𝗺𝗮𝗻𝗱 𝗧𝗲𝗰𝗵 𝗦𝗸𝗶𝗹𝗹𝘀😍

🚀 Want to future-proof your career without spending a single rupee?💵

These 6 free online courses from top institutions like Google, Harvard, IBM, Stanford, and Cisco will help you master high-demand tech skills in 2025 — from Data Analytics to Machine Learning📊🧑‍💻

𝐋𝐢𝐧𝐤👇:-

https://pdlink.in/4fbDejW

Each course is beginner-friendly, comes with certification, and helps you build your resume or switch careers✅️

Top 5 data analysis interview questions with answers 😄👇

Question 1: How would you approach a new data analysis project?

Ideal answer:
I would approach a new data analysis project by following these steps:
Understand the business goals. What is the purpose of the data analysis? What questions are we trying to answer?
Gather the data. This may involve collecting data from different sources, such as databases, spreadsheets, and surveys.
Clean and prepare the data. This may involve removing duplicate data, correcting errors, and formatting the data in a consistent way.
Explore the data. This involves using data visualization and statistical analysis to understand the data and identify any patterns or trends.
Build a model or hypothesis. This involves using the data to develop a model or hypothesis that can be used to answer the business questions.
Test the model or hypothesis. This involves using the data to test the model or hypothesis and see how well it performs.
Interpret and communicate the results. This involves explaining the results of the data analysis to stakeholders in a clear and concise way.

Question 2: What are some of the challenges you have faced in previous data analysis projects, and how did you overcome them?

Ideal answer:
One of the biggest challenges I have faced in previous data analysis projects is dealing with missing data. I have overcome this challenge by using a variety of techniques, such as imputation and machine learning.
Another challenge I have faced is dealing with large datasets. I have overcome this challenge by using efficient data processing techniques and by using cloud computing platforms.

Question 3: Can you describe a time when you used data analysis to solve a business problem?

Ideal answer:
In my previous role at a retail company, I was tasked with identifying the products that were most likely to be purchased together. I used data analysis to identify patterns in the purchase data and to develop a model that could predict which products were most likely to be purchased together. This model was used to improve the company's product recommendations and to increase sales.

Question 4: What are some of your favorite data analysis tools and techniques?

Ideal answer:
Some of my favorite data analysis tools and techniques include:
Programming languages such as Python and R
Data visualization tools such as Tableau and Power BI
Statistical analysis tools such as SPSS and SAS
Machine learning algorithms such as linear regression and decision trees

Question 5: How do you stay up-to-date on the latest trends and developments in data analysis?

Ideal answer:
I stay up-to-date on the latest trends and developments in data analysis by reading industry publications, attending conferences, and taking online courses. I also follow thought leaders on social media and subscribe to newsletters.

By providing thoughtful and well-informed answers to these questions, you can demonstrate to your interviewer that you have the analytical skills and knowledge necessary to be successful in the role.

Like this post if you want more interview questions with detailed answers to be posted in the channel 👍❤️

Share with credits: https://t.me/sqlspecialist

Hope it helps :)

🚀𝗧𝗼𝗽 𝟯 𝗙𝗿𝗲𝗲 𝗚𝗼𝗼𝗴𝗹𝗲-𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗲𝗱 𝗣𝘆𝘁𝗵𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝟮𝟬𝟮𝟱😍

Want to boost your tech career? Learn Python for FREE with Google-certified courses!
Perfect for beginners—no expensive bootcamps needed.

🔥 Learn Python for AI, Data, Automation & More!

📍𝗦𝘁𝗮𝗿𝘁 𝗡𝗼𝘄👇

https://pdlink.in/42okGqG

✅ Future You Will Thank You!

📢 We’re Hiring: Senior Data Scientist (SDS) | 2.5–3.5 Years of Experience
We’re looking for high-caliber Senior Data Scientists to join our team at Sigmoid Analytics — individuals with a passion for solving real-world business problems using scalable machine learning solutions.
If you thrive in a high-performance environment and have experience building data products end-to-end, we want to hear from you!

✅ What We’re Looking For:
2.5–3.5 years of hands-on experience in data science & machine learning
Proficient in Python and ML libraries
Experience in building and deploying ML models in production
Excellent communication skills & business understanding

🎓 From Tier-1 / Tier-2 Engineering Colleges only

📍 Location: Whitefield, Bangalore
🚫 Note: Candidates who interviewed with Sigmoid in the last 6 months are not eligible.

📬 To Apply:
Email your CV and the following details to anu.s@sigmoidanalytics.com
Years of experience
Current CTC
Expected CTC
Notice period

𝗧𝗵𝗲 𝗕𝗲𝘀𝘁 𝗙𝗿𝗲𝗲 𝟯𝟬-𝗗𝗮𝘆 𝗥𝗼𝗮𝗱𝗺𝗮𝗽 𝘁𝗼 𝗦𝘁𝗮𝗿𝘁 𝗬𝗼𝘂𝗿 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗝𝗼𝘂𝗿𝗻𝗲𝘆😍

📊 If I had to restart my Data Science journey in 2025, this is where I’d begin✨️

Meet 30 Days of Data Science — a free and beginner-friendly GitHub repository that guides you through the core fundamentals of data science in just one month🧑‍🎓📌

𝐋𝐢𝐧𝐤👇:-

https://pdlink.in/4mfNdXR

Simply bookmark the page, pick Day 1, and begin your journey✅️

𝟳 𝗠𝘂𝘀𝘁-𝗞𝗻𝗼𝘄 𝗦𝗤𝗟 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀 𝗘𝘃𝗲𝗿𝘆 𝗔𝘀𝗽𝗶𝗿𝗶𝗻𝗴 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝘁 𝗦𝗵𝗼𝘂𝗹𝗱 𝗠𝗮𝘀𝘁𝗲𝗿😍

If you’re serious about becoming a data analyst, there’s no skipping SQL. It’s not just another technical skill — it’s the core language for data analytics.📊

𝐋𝐢𝐧𝐤👇:-

https://pdlink.in/44S3Xi5

This guide covers 7 key SQL concepts that every beginner must learn✅️

Some essential concepts every data scientist should understand:

### 1. Statistics and Probability
- Purpose: Understanding data distributions and making inferences.
- Core Concepts: Descriptive statistics (mean, median, mode), inferential statistics, probability distributions (normal, binomial), hypothesis testing, p-values, confidence intervals.

### 2. Programming Languages
- Purpose: Implementing data analysis and machine learning algorithms.
- Popular Languages: Python, R.
- Libraries: NumPy, Pandas, Scikit-learn (Python), dplyr, ggplot2 (R).

### 3. Data Wrangling
- Purpose: Cleaning and transforming raw data into a usable format.
- Techniques: Handling missing values, data normalization, feature engineering, data aggregation.

### 4. Exploratory Data Analysis (EDA)
- Purpose: Summarizing the main characteristics of a dataset, often using visual methods.
- Tools: Matplotlib, Seaborn (Python), ggplot2 (R).
- Techniques: Histograms, scatter plots, box plots, correlation matrices.

### 5. Machine Learning
- Purpose: Building models to make predictions or find patterns in data.
- Core Concepts: Supervised learning (regression, classification), unsupervised learning (clustering, dimensionality reduction), model evaluation (accuracy, precision, recall, F1 score).
- Algorithms: Linear regression, logistic regression, decision trees, random forests, support vector machines, k-means clustering, principal component analysis (PCA).

### 6. Deep Learning
- Purpose: Advanced machine learning techniques using neural networks.
- Core Concepts: Neural networks, backpropagation, activation functions, overfitting, dropout.
- Frameworks: TensorFlow, Keras, PyTorch.

### 7. Natural Language Processing (NLP)
- Purpose: Analyzing and modeling textual data.
- Core Concepts: Tokenization, stemming, lemmatization, TF-IDF, word embeddings.
- Techniques: Sentiment analysis, topic modeling, named entity recognition (NER).

### 8. Data Visualization
- Purpose: Communicating insights through graphical representations.
- Tools: Matplotlib, Seaborn, Plotly (Python), ggplot2, Shiny (R), Tableau.
- Techniques: Bar charts, line graphs, heatmaps, interactive dashboards.

### 9. Big Data Technologies
- Purpose: Handling and analyzing large volumes of data.
- Technologies: Hadoop, Spark.
- Core Concepts: Distributed computing, MapReduce, parallel processing.

### 10. Databases
- Purpose: Storing and retrieving data efficiently.
- Types: SQL databases (MySQL, PostgreSQL), NoSQL databases (MongoDB, Cassandra).
- Core Concepts: Querying, indexing, normalization, transactions.

### 11. Time Series Analysis
- Purpose: Analyzing data points collected or recorded at specific time intervals.
- Core Concepts: Trend analysis, seasonal decomposition, ARIMA models, exponential smoothing.

### 12. Model Deployment and Productionization
- Purpose: Integrating machine learning models into production environments.
- Techniques: API development, containerization (Docker), model serving (Flask, FastAPI).
- Tools: MLflow, TensorFlow Serving, Kubernetes.

### 13. Data Ethics and Privacy
- Purpose: Ensuring ethical use and privacy of data.
- Core Concepts: Bias in data, ethical considerations, data anonymization, GDPR compliance.

### 14. Business Acumen
- Purpose: Aligning data science projects with business goals.
- Core Concepts: Understanding key performance indicators (KPIs), domain knowledge, stakeholder communication.

### 15. Collaboration and Version Control
- Purpose: Managing code changes and collaborative work.
- Tools: Git, GitHub, GitLab.
- Practices: Version control, code reviews, collaborative development.

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

ENJOY LEARNING 👍👍