๐AstraZeneca is hiring for Data Scientist Role
Experience: 0 - 2 year's
Apply here: https://careers.astrazeneca.com/job/-/-/7684/78581782656
๐ WhatsApp Channel: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226
๐ Telegram Channel: https://t.me/addlist/4q2PYC0pH_VjZDk5
All the best! ๐๐
Experience: 0 - 2 year's
Apply here: https://careers.astrazeneca.com/job/-/-/7684/78581782656
๐ WhatsApp Channel: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226
๐ Telegram Channel: https://t.me/addlist/4q2PYC0pH_VjZDk5
All the best! ๐๐
Forwarded from AI Prompts | ChatGPT | Google Gemini | Claude
๐ช๐ถ๐ฝ๐ฟ๐ผโ๐ ๐๐ฟ๐ฒ๐ฒ ๐๐ฎ๐๐ฎ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐ฒ ๐๐ฐ๐ฐ๐ฒ๐น๐ฒ๐ฟ๐ฎ๐๐ผ๐ฟ: ๐ฌ๐ผ๐๐ฟ ๐๐ฎ๐๐-๐ง๐ฟ๐ฎ๐ฐ๐ธ ๐๐ผ ๐ฎ ๐๐ฎ๐๐ฎ ๐๐ฎ๐ฟ๐ฒ๐ฒ๐ฟ!๐
Want to break into Data Science but donโt have a degree or years of experience? Wipro just made it easier than ever!๐จโ๐โจ๏ธ
With the Wipro Data Science Accelerator, you can start learning for FREEโno fancy credentials needed. Whether youโre a beginner or an aspiring data professional๐จโ๐ป๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/4hOXcR7
Ready to start? Explore Wiproโs Data Science Accelerator hereโ ๏ธ
Want to break into Data Science but donโt have a degree or years of experience? Wipro just made it easier than ever!๐จโ๐โจ๏ธ
With the Wipro Data Science Accelerator, you can start learning for FREEโno fancy credentials needed. Whether youโre a beginner or an aspiring data professional๐จโ๐ป๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/4hOXcR7
Ready to start? Explore Wiproโs Data Science Accelerator hereโ ๏ธ
โค1
UiPath is hiring Machine Learning Engineer
For 2022, 2023, 2024, 2025 grads
Location: Jaipur
https://jobs.ashbyhq.com/uipath/72b31ba5-168c-4edc-983a-e9a9a0c508c8
๐ WhatsApp Channel: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226
๐ Telegram Channel: https://t.me/addlist/4q2PYC0pH_VjZDk5
All the best! ๐๐
For 2022, 2023, 2024, 2025 grads
Location: Jaipur
https://jobs.ashbyhq.com/uipath/72b31ba5-168c-4edc-983a-e9a9a0c508c8
๐ WhatsApp Channel: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226
๐ Telegram Channel: https://t.me/addlist/4q2PYC0pH_VjZDk5
All the best! ๐๐
Forwarded from AI Prompts | ChatGPT | Google Gemini | Claude
๐๐ถ๐ฑ๐ฑ๐ฒ๐ป ๐๐ฒ๐บ ๐ณ๐ผ๐ฟ ๐๐ฟ๐ฒ๐ฒ ๐๐ผ๐๐ฟ๐๐ฒ๐ ๐ณ๐ฟ๐ผ๐บ ๐ ๐๐ง, ๐๐ฎ๐ฟ๐๐ฎ๐ฟ๐ฑ & ๐ฆ๐๐ฎ๐ป๐ณ๐ผ๐ฟ๐ฑ!๐
Still searching for quality learning resources?๐
What if I told you thereโs a platform offering free full-length courses from top universities like MIT, Stanford, and Harvard โ and most people have never even heard of it? ๐คฏ
๐๐ถ๐ป๐ธ๐:-๐
https://pdlink.in/4lN7aF1
Donโt skip this chanceโ ๏ธ
Still searching for quality learning resources?๐
What if I told you thereโs a platform offering free full-length courses from top universities like MIT, Stanford, and Harvard โ and most people have never even heard of it? ๐คฏ
๐๐ถ๐ป๐ธ๐:-๐
https://pdlink.in/4lN7aF1
Donโt skip this chanceโ ๏ธ
โค1
๐ Best Data Analytics Roles Based on Your Graduation Background!
Thinking about a career in Data Analytics but unsure which role fits your background? Check out these top job roles based on your degree:
๐ For Mathematics/Statistics Graduates:
๐น Data Analyst
๐น Statistical Analyst
๐น Quantitative Analyst
๐น Risk Analyst
๐ For Computer Science/IT Graduates:
๐น Data Scientist
๐น Business Intelligence Developer
๐น Data Engineer
๐น Data Architect
๐ For Economics/Finance Graduates:
๐น Financial Analyst
๐น Market Research Analyst
๐น Economic Consultant
๐น Data Journalist
๐ For Business/Management Graduates:
๐น Business Analyst
๐น Operations Research Analyst
๐น Marketing Analytics Manager
๐น Supply Chain Analyst
๐ For Engineering Graduates:
๐น Data Scientist
๐น Industrial Engineer
๐น Operations Research Analyst
๐น Quality Engineer
๐ For Social Science Graduates:
๐น Data Analyst
๐น Research Assistant
๐น Social Media Analyst
๐น Public Health Analyst
๐ For Biology/Healthcare Graduates:
๐น Clinical Data Analyst
๐น Biostatistician
๐น Research Coordinator
๐น Healthcare Consultant
โ Pro Tip:
Some of these roles may require additional certifications or upskilling in SQL, Python, Power BI, Tableau, or Machine Learning to stand out in the job market.
Like if it helps โค๏ธ
Thinking about a career in Data Analytics but unsure which role fits your background? Check out these top job roles based on your degree:
๐ For Mathematics/Statistics Graduates:
๐น Data Analyst
๐น Statistical Analyst
๐น Quantitative Analyst
๐น Risk Analyst
๐ For Computer Science/IT Graduates:
๐น Data Scientist
๐น Business Intelligence Developer
๐น Data Engineer
๐น Data Architect
๐ For Economics/Finance Graduates:
๐น Financial Analyst
๐น Market Research Analyst
๐น Economic Consultant
๐น Data Journalist
๐ For Business/Management Graduates:
๐น Business Analyst
๐น Operations Research Analyst
๐น Marketing Analytics Manager
๐น Supply Chain Analyst
๐ For Engineering Graduates:
๐น Data Scientist
๐น Industrial Engineer
๐น Operations Research Analyst
๐น Quality Engineer
๐ For Social Science Graduates:
๐น Data Analyst
๐น Research Assistant
๐น Social Media Analyst
๐น Public Health Analyst
๐ For Biology/Healthcare Graduates:
๐น Clinical Data Analyst
๐น Biostatistician
๐น Research Coordinator
๐น Healthcare Consultant
โ Pro Tip:
Some of these roles may require additional certifications or upskilling in SQL, Python, Power BI, Tableau, or Machine Learning to stand out in the job market.
Like if it helps โค๏ธ
โค1
Data Engineering Roles @ MathCo! ๐จ
We're building cutting-edge solutions across cloud, data, and product ecosystemsโand weโre looking for exceptional talent to join our growing engineering team.
If you're excited by real-world impact, solving complex data problems, and working alongside some of the sharpest minds in the industry, letโs connect.
Open Roles:
1. Cloud Engineer โ II
Design and manage cloud-native data infrastructure, optimize pipelines, and solve complex ETL challenges using SQL and modern cloud platforms.
2. Senior Data Engineer
Lead PoCs/PoVs and scale reliable data systems across cloud, batch, and real-time architectures.
3. Lead Data Engineer
Architect scalable pipelines, collaborate with cross-functional teams, and lead delivery of end-to-end, business-aligned solutions.
4. Engineering Manager
Drive strategy, mentor high-performing teams, and lead the delivery of high-impact outcomes across the modern data stack.
๐Location: Bangalore
๐ฉ Interested? Drop your CV at arvind.pothula@mathco.com
We're building cutting-edge solutions across cloud, data, and product ecosystemsโand weโre looking for exceptional talent to join our growing engineering team.
If you're excited by real-world impact, solving complex data problems, and working alongside some of the sharpest minds in the industry, letโs connect.
Open Roles:
1. Cloud Engineer โ II
Design and manage cloud-native data infrastructure, optimize pipelines, and solve complex ETL challenges using SQL and modern cloud platforms.
2. Senior Data Engineer
Lead PoCs/PoVs and scale reliable data systems across cloud, batch, and real-time architectures.
3. Lead Data Engineer
Architect scalable pipelines, collaborate with cross-functional teams, and lead delivery of end-to-end, business-aligned solutions.
4. Engineering Manager
Drive strategy, mentor high-performing teams, and lead the delivery of high-impact outcomes across the modern data stack.
๐Location: Bangalore
๐ฉ Interested? Drop your CV at arvind.pothula@mathco.com
โค2
Forwarded from Python for Data Analysts
๐ช๐ฎ๐ป๐ ๐๐ผ ๐ฃ๐ฟ๐ผ๐๐ฒ ๐ฌ๐ผ๐๐ฟ ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐ถ๐ฐ๐ ๐ฆ๐ธ๐ถ๐น๐น๐ ๐ช๐ถ๐๐ต๐ผ๐๐ ๐ฆ๐ฝ๐ฒ๐ป๐ฑ๐ถ๐ป๐ด ๐ฎ ๐ฅ๐๐ฝ๐ฒ๐ฒ?๐
Knowledge is powerful โ but certifications show proof. Whether youโre applying for internships, jobs, or freelance roles, having verifiable credentials in Python, SQL, and Data Visualization can set you apart.๐๐ซ
๐๐ข๐ง๐ค๐:-
https://pdlink.in/4eNiUVP
Enjoy Learning โ ๏ธ
Knowledge is powerful โ but certifications show proof. Whether youโre applying for internships, jobs, or freelance roles, having verifiable credentials in Python, SQL, and Data Visualization can set you apart.๐๐ซ
๐๐ข๐ง๐ค๐:-
https://pdlink.in/4eNiUVP
Enjoy Learning โ ๏ธ
The Only SQL You Actually Need For Your First Job (Data Analytics)
The Learning Trap: What Most Beginners Fall Into
When starting out, it's common to feel like you need to master every possible SQL concept. You binge YouTube videos, tutorials, and courses, yet still feel lost in interviews or when given a real dataset.
Common traps:
- Complex subqueries
- Advanced CTEs
- Recursive queries
- 100+ tutorials watched
- 0 practical experience
Reality Check: What You'll Actually Use 75% of the Time
Most data analytics roles (especially entry-level) require clarity, speed, and confidence with core SQL operations. Hereโs what covers most daily work:
1. SELECT, FROM, WHERE โ The Foundation
SELECT name, age
FROM employees
WHERE department = 'Finance';
This is how almost every query begins. Whether exploring a dataset or building a dashboard, these are always in use.
2. JOINs โ Combining Data From Multiple Tables
SELECT e.name, d.department_name
FROM employees e
JOIN departments d ON e.department_id = d.id;
Youโll often join tables like employee data with department, customer orders with payments, etc.
3. GROUP BY โ Summarizing Data
SELECT department, COUNT(*) AS employee_count
FROM employees
GROUP BY department;
Used to get summaries by categories like sales per region or users by plan.
4. ORDER BY โ Sorting Results
SELECT name, salary
FROM employees
ORDER BY salary DESC;
Helps sort output for dashboards or reports.
5. Aggregations โ Simple But Powerful
Common functions: COUNT(), SUM(), AVG(), MIN(), MAX()
SELECT AVG(salary)
FROM employees
WHERE department = 'IT';
Gives quick insights like average deal size or total revenue.
6. ROW_NUMBER() โ Adding Row Logic
SELECT *
FROM (
SELECT *, ROW_NUMBER() OVER(PARTITION BY customer_id ORDER BY order_date DESC) as rn
FROM orders
) sub
WHERE rn = 1;
Used for deduplication, rankings, or selecting the latest record per group.
Credits: https://whatsapp.com/channel/0029VaGgzAk72WTmQFERKh02
React โค๏ธ for more
The Learning Trap: What Most Beginners Fall Into
When starting out, it's common to feel like you need to master every possible SQL concept. You binge YouTube videos, tutorials, and courses, yet still feel lost in interviews or when given a real dataset.
Common traps:
- Complex subqueries
- Advanced CTEs
- Recursive queries
- 100+ tutorials watched
- 0 practical experience
Reality Check: What You'll Actually Use 75% of the Time
Most data analytics roles (especially entry-level) require clarity, speed, and confidence with core SQL operations. Hereโs what covers most daily work:
1. SELECT, FROM, WHERE โ The Foundation
SELECT name, age
FROM employees
WHERE department = 'Finance';
This is how almost every query begins. Whether exploring a dataset or building a dashboard, these are always in use.
2. JOINs โ Combining Data From Multiple Tables
SELECT e.name, d.department_name
FROM employees e
JOIN departments d ON e.department_id = d.id;
Youโll often join tables like employee data with department, customer orders with payments, etc.
3. GROUP BY โ Summarizing Data
SELECT department, COUNT(*) AS employee_count
FROM employees
GROUP BY department;
Used to get summaries by categories like sales per region or users by plan.
4. ORDER BY โ Sorting Results
SELECT name, salary
FROM employees
ORDER BY salary DESC;
Helps sort output for dashboards or reports.
5. Aggregations โ Simple But Powerful
Common functions: COUNT(), SUM(), AVG(), MIN(), MAX()
SELECT AVG(salary)
FROM employees
WHERE department = 'IT';
Gives quick insights like average deal size or total revenue.
6. ROW_NUMBER() โ Adding Row Logic
SELECT *
FROM (
SELECT *, ROW_NUMBER() OVER(PARTITION BY customer_id ORDER BY order_date DESC) as rn
FROM orders
) sub
WHERE rn = 1;
Used for deduplication, rankings, or selecting the latest record per group.
Credits: https://whatsapp.com/channel/0029VaGgzAk72WTmQFERKh02
React โค๏ธ for more
โค1
Atlassian hiring Data Engineer
Apply link: https://careers-apac-atlassian.icims.com/jobs/19687/data-engineer/job?iis=LinkedIn&iisn=LinkedIn_Job_Ad
Apply link: https://careers-apac-atlassian.icims.com/jobs/19687/data-engineer/job?iis=LinkedIn&iisn=LinkedIn_Job_Ad
Australia | India Careers (External)
Data Engineer in | Careers at Remote - India
Working at Atlassian
Atlassians can choose where they work โ whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in anyโฆ
Atlassians can choose where they work โ whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in anyโฆ
Atlassian is hiring Machine Learning Engineer
For 2021, 2022, 2023 grads
Location: Bangalore
https://www.atlassian.com/company/careers
For 2021, 2022, 2023 grads
Location: Bangalore
https://www.atlassian.com/company/careers
Atlassian
Atlassian Careers: Join the Team | Atlassian
Explore Atlassian career opportunities, our teams, as well as benefits and perks!
โค2
Forwarded from AI Prompts | ChatGPT | Google Gemini | Claude
๐๐ฎ๐๐ป๐ฐ๐ต ๐ฌ๐ผ๐๐ฟ ๐ง๐ฒ๐ฐ๐ต ๐๐ฎ๐ฟ๐ฒ๐ฒ๐ฟ ๐ถ๐ป ๐ฎ๐ฌ๐ฎ๐ฑ โ ๐ช๐ถ๐๐ต ๐ ๐ถ๐ฐ๐ฟ๐ผ๐๐ผ๐ณ๐โ๐ ๐๐ฟ๐ฒ๐ฒ ๐๐ฒ๐ฎ๐ฟ๐ป๐ถ๐ป๐ด ๐ฃ๐ฎ๐๐ต๐!๐
Looking to start a career in tech but confused about where to begin? ๐ป
Microsoftโs free learning platform is designed just for you โ offering structured, beginner-friendly career paths for roles๐๐จโ๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/4lpckY3
No confusion. No hidden fees. Just future-proof learning that worksโ ๏ธ
Looking to start a career in tech but confused about where to begin? ๐ป
Microsoftโs free learning platform is designed just for you โ offering structured, beginner-friendly career paths for roles๐๐จโ๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/4lpckY3
No confusion. No hidden fees. Just future-proof learning that worksโ ๏ธ
โค1
Data Science Learning Plan
Step 1: Mathematics for Data Science (Statistics, Probability, Linear Algebra)
Step 2: Python for Data Science (Basics and Libraries)
Step 3: Data Manipulation and Analysis (Pandas, NumPy)
Step 4: Data Visualization (Matplotlib, Seaborn, Plotly)
Step 5: Databases and SQL for Data Retrieval
Step 6: Introduction to Machine Learning (Supervised and Unsupervised Learning)
Step 7: Data Cleaning and Preprocessing
Step 8: Feature Engineering and Selection
Step 9: Model Evaluation and Tuning
Step 10: Deep Learning (Neural Networks, TensorFlow, Keras)
Step 11: Working with Big Data (Hadoop, Spark)
Step 12: Building Data Science Projects and Portfolio
Data Science Resources
๐๐
https://whatsapp.com/channel/0029Va4QUHa6rsQjhITHK82y
Like for more ๐
Step 1: Mathematics for Data Science (Statistics, Probability, Linear Algebra)
Step 2: Python for Data Science (Basics and Libraries)
Step 3: Data Manipulation and Analysis (Pandas, NumPy)
Step 4: Data Visualization (Matplotlib, Seaborn, Plotly)
Step 5: Databases and SQL for Data Retrieval
Step 6: Introduction to Machine Learning (Supervised and Unsupervised Learning)
Step 7: Data Cleaning and Preprocessing
Step 8: Feature Engineering and Selection
Step 9: Model Evaluation and Tuning
Step 10: Deep Learning (Neural Networks, TensorFlow, Keras)
Step 11: Working with Big Data (Hadoop, Spark)
Step 12: Building Data Science Projects and Portfolio
Data Science Resources
๐๐
https://whatsapp.com/channel/0029Va4QUHa6rsQjhITHK82y
Like for more ๐
โค4
1: How would you preprocess and tokenize text data from tweets for sentiment analysis? Discuss potential challenges and solutions.
- Answer: Preprocessing and tokenizing text data for sentiment analysis involves tasks like lowercasing, removing stop words, and stemming or lemmatization. Handling challenges like handling emojis, slang, and noisy text is crucial. Tools like NLTK or spaCy can assist in these tasks.
2: Explain the collaborative filtering approach in building recommendation systems. How might Twitter use this to enhance user experience?
- Answer: Collaborative filtering recommends items based on user preferences and similarities. Techniques include user-based or item-based collaborative filtering and matrix factorization. Twitter could leverage user interactions to recommend tweets, users, or topics.
3: Write a Python or Scala function to count the frequency of hashtags in a given collection of tweets.
- Answer (Python):
4: How does graph analysis contribute to understanding user interactions and content propagation on Twitter? Provide a specific use case.
- Answer: Graph analysis on Twitter involves examining user interactions. For instance, identifying influential users or detecting communities based on retweet or mention networks. Algorithms like PageRank or Louvain Modularity can aid in these analyses.
- Answer: Preprocessing and tokenizing text data for sentiment analysis involves tasks like lowercasing, removing stop words, and stemming or lemmatization. Handling challenges like handling emojis, slang, and noisy text is crucial. Tools like NLTK or spaCy can assist in these tasks.
2: Explain the collaborative filtering approach in building recommendation systems. How might Twitter use this to enhance user experience?
- Answer: Collaborative filtering recommends items based on user preferences and similarities. Techniques include user-based or item-based collaborative filtering and matrix factorization. Twitter could leverage user interactions to recommend tweets, users, or topics.
3: Write a Python or Scala function to count the frequency of hashtags in a given collection of tweets.
- Answer (Python):
def count_hashtags(tweet_collection):
hashtags_count = {}
for tweet in tweet_collection:
hashtags = [word for word in tweet.split() if word.startswith('#')]
for hashtag in hashtags:
hashtags_count[hashtag] = hashtags_count.get(hashtag, 0) + 1
return hashtags_count
4: How does graph analysis contribute to understanding user interactions and content propagation on Twitter? Provide a specific use case.
- Answer: Graph analysis on Twitter involves examining user interactions. For instance, identifying influential users or detecting communities based on retweet or mention networks. Algorithms like PageRank or Louvain Modularity can aid in these analyses.
โค2
Forwarded from AI Prompts | ChatGPT | Google Gemini | Claude
๐ฒ ๐๐ฟ๐ฒ๐ฒ ๐๐ผ๐๐ฟ๐๐ฒ๐ ๐๐ผ ๐ฆ๐๐ฎ๐ฟ๐ ๐ฌ๐ผ๐๐ฟ ๐๐ฎ๐๐ฎ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐ฒ & ๐๐ป๐ฎ๐น๐๐๐ถ๐ฐ๐ ๐๐ผ๐๐ฟ๐ป๐ฒ๐๐
Want to break into Data Science & Analytics but donโt want to spend on expensive courses?๐จโ๐ป
Start here โ with 100% FREE courses from Cisco, IBM, Google & LinkedIn, all with certificates you can showcase on LinkedIn or your resume!๐๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/3Ix2oxd
This list will set you up with real-world, job-ready skillsโ ๏ธ
Want to break into Data Science & Analytics but donโt want to spend on expensive courses?๐จโ๐ป
Start here โ with 100% FREE courses from Cisco, IBM, Google & LinkedIn, all with certificates you can showcase on LinkedIn or your resume!๐๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/3Ix2oxd
This list will set you up with real-world, job-ready skillsโ ๏ธ
โค1
Forwarded from AI Prompts | ChatGPT | Google Gemini | Claude
๐๐ฟ๐ฎ๐ฐ๐ธ ๐๐๐๐ก๐ ๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐๐ ๐ถ๐ป ๐ฎ๐ฌ๐ฎ๐ฑ โ ๐ณ๐ผ๐ฟ ๐๐ฅ๐๐!๐
If youโre serious about cracking top tech interviews โ from FAANG to startups โ this is the roadmap you canโt afford to miss๐
Thousands have used it to land roles at Google, Amazon, Microsoft, and more โ completely free๐คฉ๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/3TJlpyW
Your dream job might just start here.โ ๏ธ
If youโre serious about cracking top tech interviews โ from FAANG to startups โ this is the roadmap you canโt afford to miss๐
Thousands have used it to land roles at Google, Amazon, Microsoft, and more โ completely free๐คฉ๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/3TJlpyW
Your dream job might just start here.โ ๏ธ
โค1