๐ง Technologies for Data Analysts!
๐ Data Manipulation & Analysis
โช๏ธ Excel โ Spreadsheet Data Analysis & Visualization
โช๏ธ SQL โ Structured Query Language for Data Extraction
โช๏ธ Pandas (Python) โ Data Analysis with DataFrames
โช๏ธ NumPy (Python) โ Numerical Computing for Large Datasets
โช๏ธ Google Sheets โ Online Collaboration for Data Analysis
๐ Data Visualization
โช๏ธ Power BI โ Business Intelligence & Dashboarding
โช๏ธ Tableau โ Interactive Data Visualization
โช๏ธ Matplotlib (Python) โ Plotting Graphs & Charts
โช๏ธ Seaborn (Python) โ Statistical Data Visualization
โช๏ธ Google Data Studio โ Free, Web-Based Visualization Tool
๐ ETL (Extract, Transform, Load)
โช๏ธ SQL Server Integration Services (SSIS) โ Data Integration & ETL
โช๏ธ Apache NiFi โ Automating Data Flows
โช๏ธ Talend โ Data Integration for Cloud & On-premises
๐งน Data Cleaning & Preparation
โช๏ธ OpenRefine โ Clean & Transform Messy Data
โช๏ธ Pandas Profiling (Python) โ Data Profiling & Preprocessing
โช๏ธ DataWrangler โ Data Transformation Tool
๐ฆ Data Storage & Databases
โช๏ธ SQL โ Relational Databases (MySQL, PostgreSQL, MS SQL)
โช๏ธ NoSQL (MongoDB) โ Flexible, Schema-less Data Storage
โช๏ธ Google BigQuery โ Scalable Cloud Data Warehousing
โช๏ธ Redshift โ Amazonโs Cloud Data Warehouse
โ๏ธ Data Automation
โช๏ธ Alteryx โ Data Blending & Advanced Analytics
โช๏ธ Knime โ Data Analytics & Reporting Automation
โช๏ธ Zapier โ Connect & Automate Data Workflows
๐ Advanced Analytics & Statistical Tools
โช๏ธ R โ Statistical Computing & Analysis
โช๏ธ Python (SciPy, Statsmodels) โ Statistical Modeling & Hypothesis Testing
โช๏ธ SPSS โ Statistical Software for Data Analysis
โช๏ธ SAS โ Advanced Analytics & Predictive Modeling
๐ Collaboration & Reporting
โช๏ธ Power BI Service โ Online Sharing & Collaboration for Dashboards
โช๏ธ Tableau Online โ Cloud-Based Visualization & Sharing
โช๏ธ Google Analytics โ Web Traffic Data Insights
โช๏ธ Trello / JIRA โ Project & Task Management for Data Projects
Data-Driven Decisions with the Right Tools!
React โค๏ธ for more
๐ Data Manipulation & Analysis
โช๏ธ Excel โ Spreadsheet Data Analysis & Visualization
โช๏ธ SQL โ Structured Query Language for Data Extraction
โช๏ธ Pandas (Python) โ Data Analysis with DataFrames
โช๏ธ NumPy (Python) โ Numerical Computing for Large Datasets
โช๏ธ Google Sheets โ Online Collaboration for Data Analysis
๐ Data Visualization
โช๏ธ Power BI โ Business Intelligence & Dashboarding
โช๏ธ Tableau โ Interactive Data Visualization
โช๏ธ Matplotlib (Python) โ Plotting Graphs & Charts
โช๏ธ Seaborn (Python) โ Statistical Data Visualization
โช๏ธ Google Data Studio โ Free, Web-Based Visualization Tool
๐ ETL (Extract, Transform, Load)
โช๏ธ SQL Server Integration Services (SSIS) โ Data Integration & ETL
โช๏ธ Apache NiFi โ Automating Data Flows
โช๏ธ Talend โ Data Integration for Cloud & On-premises
๐งน Data Cleaning & Preparation
โช๏ธ OpenRefine โ Clean & Transform Messy Data
โช๏ธ Pandas Profiling (Python) โ Data Profiling & Preprocessing
โช๏ธ DataWrangler โ Data Transformation Tool
๐ฆ Data Storage & Databases
โช๏ธ SQL โ Relational Databases (MySQL, PostgreSQL, MS SQL)
โช๏ธ NoSQL (MongoDB) โ Flexible, Schema-less Data Storage
โช๏ธ Google BigQuery โ Scalable Cloud Data Warehousing
โช๏ธ Redshift โ Amazonโs Cloud Data Warehouse
โ๏ธ Data Automation
โช๏ธ Alteryx โ Data Blending & Advanced Analytics
โช๏ธ Knime โ Data Analytics & Reporting Automation
โช๏ธ Zapier โ Connect & Automate Data Workflows
๐ Advanced Analytics & Statistical Tools
โช๏ธ R โ Statistical Computing & Analysis
โช๏ธ Python (SciPy, Statsmodels) โ Statistical Modeling & Hypothesis Testing
โช๏ธ SPSS โ Statistical Software for Data Analysis
โช๏ธ SAS โ Advanced Analytics & Predictive Modeling
๐ Collaboration & Reporting
โช๏ธ Power BI Service โ Online Sharing & Collaboration for Dashboards
โช๏ธ Tableau Online โ Cloud-Based Visualization & Sharing
โช๏ธ Google Analytics โ Web Traffic Data Insights
โช๏ธ Trello / JIRA โ Project & Task Management for Data Projects
Data-Driven Decisions with the Right Tools!
React โค๏ธ for more
โค1
Forwarded from Python Projects & Resources
๐ญ๐ฌ๐ฌ% ๐๐ฟ๐ฒ๐ฒ ๐ง๐ฒ๐ฐ๐ต ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐๐ผ๐๐ฟ๐๐ฒ๐๐
From data science and AI to web development and cloud computing, checkout Top 5 Websites for Free Tech Certification Courses in 2025
๐๐ข๐ง๐ค๐:-
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Enroll For FREE & Get Certified!โ ๏ธ
From data science and AI to web development and cloud computing, checkout Top 5 Websites for Free Tech Certification Courses in 2025
๐๐ข๐ง๐ค๐:-
https://pdlink.in/4e76jMX
Enroll For FREE & Get Certified!โ ๏ธ
โค1
Forwarded from Artificial Intelligence
๐ฑ ๐๐ฟ๐ฒ๐ฒ ๐ฅ๐ฒ๐๐ผ๐๐ฟ๐ฐ๐ฒ๐ ๐๐ผ ๐๐ฒ๐ฎ๐ฟ๐ป ๐ ๐ฎ๐ฐ๐ต๐ถ๐ป๐ฒ ๐๐ฒ๐ฎ๐ฟ๐ป๐ถ๐ป๐ด ๐ณ๐ฟ๐ผ๐บ ๐ฆ๐ฐ๐ฟ๐ฎ๐๐ฐ๐ต ๐ถ๐ป ๐ฎ๐ฌ๐ฎ๐ฑ๐
๐ฏ Want to break into Machine Learning but donโt know where to start?โจ๏ธ
You donโt need a fancy degree or expensive course to begin your ML journey๐
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This list is for anyone ready to start learning ML from scratchโ ๏ธ
๐ฏ Want to break into Machine Learning but donโt know where to start?โจ๏ธ
You donโt need a fancy degree or expensive course to begin your ML journey๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/4jRouYb
This list is for anyone ready to start learning ML from scratchโ ๏ธ
10 ChatGPT Prompts for Marketing You'll Actually Use:
1. Crafting a Brand Story
Prompt: "Develop an engaging brand story and persona for [company name] that authentically conveys our mission, values, and competitive differentiation."
2. Optimizing Landing Pages
Prompt: "Optimize the landing page for [product/service page name] to immediately convey value, build trust, and motivate visitors to convert."
3. Generating Content Ideas
Prompt: "Suggest 10 compelling content ideas related to [topic/keyword] that will engage our target audience and promote brand awareness."
4. Improving SEO
Prompt: "Provide 3 strategic recommendations to improve SEO and increase organic traffic for [company name/website]."
5. Building an Email Nurture Sequence
Prompt: "Design a personalized, multi-message email nurture sequence focused on educating and converting leads interested in [product/service]."
6. Crafting Value Propositions
Prompt: "Create strong, benefit-driven value propositions highlighting the top 3 advantages of using [product/service] over competitors."
7. Producing Engaging Social Media Content
Prompt: "Develop 5 creative social media post ideas for [platform] that will resonate with our audience and align with broader campaign goals."
8. Planning an Influencer Marketing Partnership
Prompt: "Outline an influencer partnership strategy for [company] to build brand awareness and trust among our target demographic."
9. Crafting Paid Ads
Prompt: "Write high-converting Facebook/Google ads for [product/service] tailored to our unique selling proposition and audience motivations."
10. Building an Email Marketing Campaign
Prompt: "Construct a complete email marketing campaign for the launch of [product/service], including series copy, visual assets, send schedule, and success metrics."
Share with your friends: https://t.me/Learn_Startup
ENJOY LEARNING ๐๐
1. Crafting a Brand Story
Prompt: "Develop an engaging brand story and persona for [company name] that authentically conveys our mission, values, and competitive differentiation."
2. Optimizing Landing Pages
Prompt: "Optimize the landing page for [product/service page name] to immediately convey value, build trust, and motivate visitors to convert."
3. Generating Content Ideas
Prompt: "Suggest 10 compelling content ideas related to [topic/keyword] that will engage our target audience and promote brand awareness."
4. Improving SEO
Prompt: "Provide 3 strategic recommendations to improve SEO and increase organic traffic for [company name/website]."
5. Building an Email Nurture Sequence
Prompt: "Design a personalized, multi-message email nurture sequence focused on educating and converting leads interested in [product/service]."
6. Crafting Value Propositions
Prompt: "Create strong, benefit-driven value propositions highlighting the top 3 advantages of using [product/service] over competitors."
7. Producing Engaging Social Media Content
Prompt: "Develop 5 creative social media post ideas for [platform] that will resonate with our audience and align with broader campaign goals."
8. Planning an Influencer Marketing Partnership
Prompt: "Outline an influencer partnership strategy for [company] to build brand awareness and trust among our target demographic."
9. Crafting Paid Ads
Prompt: "Write high-converting Facebook/Google ads for [product/service] tailored to our unique selling proposition and audience motivations."
10. Building an Email Marketing Campaign
Prompt: "Construct a complete email marketing campaign for the launch of [product/service], including series copy, visual assets, send schedule, and success metrics."
Share with your friends: https://t.me/Learn_Startup
ENJOY LEARNING ๐๐
โค1
Forwarded from Artificial Intelligence
๐๐ฟ๐ฒ๐ฒ ๐๐ฎ๐๐ฎ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐ฒ ๐ฅ๐ผ๐ฎ๐ฑ๐บ๐ฎ๐ฝ ๐ณ๐ผ๐ฟ ๐๐ฒ๐ด๐ถ๐ป๐ป๐ฒ๐ฟ๐: ๐ฑ ๐ฆ๐๐ฒ๐ฝ๐ ๐๐ผ ๐ฆ๐๐ฎ๐ฟ๐ ๐ฌ๐ผ๐๐ฟ ๐๐ผ๐๐ฟ๐ป๐ฒ๐๐
Want to break into Data Science but donโt know where to begin?๐จโ๐ป๐
Youโre not alone. Data Science is one of the most in-demand fields today, but with so many courses online, it can feel overwhelming.๐ซ๐ฒ
๐๐ข๐ง๐ค๐:-
https://pdlink.in/3SU5FJ0
No prior experience needed!โ ๏ธ
Want to break into Data Science but donโt know where to begin?๐จโ๐ป๐
Youโre not alone. Data Science is one of the most in-demand fields today, but with so many courses online, it can feel overwhelming.๐ซ๐ฒ
๐๐ข๐ง๐ค๐:-
https://pdlink.in/3SU5FJ0
No prior experience needed!โ ๏ธ
โค2
๐ง๐ผ๐ฝ ๐ง๐ฒ๐ฐ๐ต ๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐ ๐ค๐๐ฒ๐๐๐ถ๐ผ๐ป๐ - ๐๐ฟ๐ฎ๐ฐ๐ธ ๐ฌ๐ผ๐๐ฟ ๐ก๐ฒ๐
๐ ๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐๐
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Get Your Dream Tech Job In Your Dream Company๐ซ
Coding and Aptitude Round before interview
Coding challenges are meant to test your coding skills (especially if you are applying for ML engineer role). The coding challenges can contain algorithm and data structures problems of varying difficulty. These challenges will be timed based on how complicated the questions are. These are intended to test your basic algorithmic thinking.
Sometimes, a complicated data science question like making predictions based on twitter data are also given. These challenges are hosted on HackerRank, HackerEarth, CoderByte etc. In addition, you may even be asked multiple-choice questions on the fundamentals of data science and statistics. This round is meant to be a filtering round where candidates whose fundamentals are little shaky are eliminated. These rounds are typically conducted without any manual intervention, so it is important to be well prepared for this round.
Sometimes a separate Aptitude test is conducted or along with the technical round an aptitude test is also conducted to assess your aptitude skills. A Data Scientist is expected to have a good aptitude as this field is continuously evolving and a Data Scientist encounters new challenges every day. If you have appeared for GMAT / GRE or CAT, this should be easy for you.
Resources for Prep:
For algorithms and data structures prep,Leetcode and Hackerrank are good resources.
For aptitude prep, you can refer to IndiaBixand Practice Aptitude.
With respect to data science challenges, practice well on GLabs and Kaggle.
Brilliant is an excellent resource for tricky math and statistics questions.
For practising SQL, SQL Zoo and Mode Analytics are good resources that allow you to solve the exercises in the browser itself.
Things to Note:
Ensure that you are calm and relaxed before you attempt to answer the challenge. Read through all the questions before you start attempting the same. Let your mind go into problem-solving mode before your fingers do!
In case, you are finished with the test before time, recheck your answers and then submit.
Sometimes these rounds donโt go your way, you might have had a brain fade, it was not your day etc. Donโt worry! Shake if off for there is always a next time and this is not the end of the world.
Coding challenges are meant to test your coding skills (especially if you are applying for ML engineer role). The coding challenges can contain algorithm and data structures problems of varying difficulty. These challenges will be timed based on how complicated the questions are. These are intended to test your basic algorithmic thinking.
Sometimes, a complicated data science question like making predictions based on twitter data are also given. These challenges are hosted on HackerRank, HackerEarth, CoderByte etc. In addition, you may even be asked multiple-choice questions on the fundamentals of data science and statistics. This round is meant to be a filtering round where candidates whose fundamentals are little shaky are eliminated. These rounds are typically conducted without any manual intervention, so it is important to be well prepared for this round.
Sometimes a separate Aptitude test is conducted or along with the technical round an aptitude test is also conducted to assess your aptitude skills. A Data Scientist is expected to have a good aptitude as this field is continuously evolving and a Data Scientist encounters new challenges every day. If you have appeared for GMAT / GRE or CAT, this should be easy for you.
Resources for Prep:
For algorithms and data structures prep,Leetcode and Hackerrank are good resources.
For aptitude prep, you can refer to IndiaBixand Practice Aptitude.
With respect to data science challenges, practice well on GLabs and Kaggle.
Brilliant is an excellent resource for tricky math and statistics questions.
For practising SQL, SQL Zoo and Mode Analytics are good resources that allow you to solve the exercises in the browser itself.
Things to Note:
Ensure that you are calm and relaxed before you attempt to answer the challenge. Read through all the questions before you start attempting the same. Let your mind go into problem-solving mode before your fingers do!
In case, you are finished with the test before time, recheck your answers and then submit.
Sometimes these rounds donโt go your way, you might have had a brain fade, it was not your day etc. Donโt worry! Shake if off for there is always a next time and this is not the end of the world.
โค1