# Data Science

Data Science Roadmap, Computer Science, Fundamental, Data Engineering, Python, Github, Excel, Data Analytics

# Data Scientist Roadmap

[![data_science.jpeg](https://resources.planforfailure.com/uploads/images/gallery/2024-01/scaled-1680-/ftpXmCQJWpigDD4x-data-science.jpeg)](https://resources.planforfailure.com/uploads/images/gallery/2024-01/ftpXmCQJWpigDD4x-data-science.jpeg)

1️⃣ IBM Data Science Professional Certificate  
[https://lnkd.in/d58NA5mG](https://www.coursera.org/professional-certificates/ibm-data-science)

2️⃣ Python  
[https://lnkd.in/dTjC2nER](https://www.coursera.org/learn/python-for-applied-data-science-ai)

3️⃣ R  
[https://lnkd.in/dsKRzJD3](https://www.coursera.org/learn/data-analysis-r)

4️⃣ PowerBI  
[https://lnkd.in/dZBebfSR](https://www.coursera.org/professional-certificates/microsoft-power-bi-data-analyst)

5️⃣ Mathematics  
[https://lnkd.in/ds5dHAA9](https://www.coursera.org/learn/mathematical-thinking)

6️⃣ Tableau  
[https://lnkd.in/dvfNCjNX](https://www.coursera.org/specializations/data-visualization)

7️⃣ Excel and PowerBI  
[https://lnkd.in/dBZkzcfK](https://www.coursera.org/learn/extract-transform-and-load-data-in-power-bi)

8️⃣ Probability  
[https://lnkd.in/djHqTfZm](https://www.coursera.org/learn/probability-intro)

9️⃣ Statistics  
[https://lnkd.in/dyM7rU\_g](https://www.coursera.org/learn/stanford-statistics)

🔟 Linear Algebra  
[https://lnkd.in/d2vRH4Pi](https://www.coursera.org/learn/linear-algebra-machine-learning)

11\. Machine Learning  
[https://lnkd.in/dYcB6wTQ](https://www.coursera.org/specializations/machine-learning-introduction)

12\. Deep Learning  
[https://lnkd.in/d2G5bNcs](https://www.coursera.org/specializations/deep-learning)

13\. Data Analysis  
[https://lnkd.in/dEvKPC9Q](https://www.coursera.org/professional-certificates/google-data-analytics)

14\. Data Visualization  
[https://lnkd.in/dyrCKF5A](https://www.coursera.org/learn/data-visualization-dashboards-excel-cognos)

15\. SQL  
[https://lnkd.in/d2WZDU6B](https://www.coursera.org/specializations/learn-sql-basics-data-science)

# Harvard - Computer Science

1\. Introduction to Computer Science  
  
🔗 [https://lnkd.in/gp9WvEup](https://www.edx.org/learn/computer-science/harvard-university-cs50-s-introduction-to-computer-science)  
  
2\. Introduction to Game Development  
  
🔗 [https://lnkd.in/gdJvbe6n](https://www.edx.org/learn/computer-science/hp-generative-ai-mastery-revolutionizing-game-development?index=product&queryId=3c2a4892f5d9ba26e75951217d32a25e&position=1)  
  
3\. Introduction to Programming with Scratch  
  
🔗[ https://lnkd.in/g6J2KuhD](https://www.edx.org/learn/scratch-programming/harvard-university-cs50-s-introduction-to-programming-with-scratch)  
  
4\. Web Programming with Python and JavaScript  
  
🔗 [https://lnkd.in/gzcagQqp](https://www.edx.org/learn/web-development/harvard-university-cs50-s-web-programming-with-python-and-javascript)  
  
5\. Computer Science for Business Professionals  
  
🔗[ https://lnkd.in/gMFK47PR](https://www.edx.org/learn/computer-science/harvard-university-cs50-s-computer-science-for-business-professionals)  
  
6\. CS50 for Lawyers  
  
🔗 [https://lnkd.in/gi9tUjTE](https://www.edx.org/learn/computer-science/harvard-university-cs50-s-computer-science-for-lawyers)  
  
7\. Introduction to Artificial Intelligence with Python  
  
🔗 [https://lnkd.in/gDsPqv9B](https://lnkd.in/gDsPqv9B)  
  
8\. Introduction to Programming with Python  
  
🔗 [https://lnkd.in/gAZVzHrR](https://lnkd.in/gAZVzHrR)  
  
9\. Data Science: Machine Learning  
  
🔗 [https://lnkd.in/gN2aqYAJ](https://lnkd.in/gN2aqYAJ)  
  
10\. Data Science: Productivity Tools  
  
🔗[ https://lnkd.in/g4ThxhUD](https://lnkd.in/g4ThxhUD)  
  
11\. Understanding Technology  
  
🔗[ https://lnkd.in/dwThBANS](https://lnkd.in/dwThBANS)  
  
12\. Mobile App Development with React Native  
  
🔗 [https://lnkd.in/dHWf4Gip](https://lnkd.in/dHWf4Gip)  
  
13\. Introduction to Data Science with Python  
  
🔗[ https://lnkd.in/dr9W-7GT](https://lnkd.in/dr9W-7GT)  
  
14\. Artificial Intelligence in Business: Creating Value with Machine Learning.  
  
🔗 [https://lnkd.in/gcF\_Nbsr](https://lnkd.in/gcF_Nbsr)  
  
15\. Fundamentals of TinyML  
  
🔗 [https://lnkd.in/dbd4XPUz](https://lnkd.in/dbd4XPUz)  
  
16\. CS50's Computer Science for Business Professionals   
  
🔗 [https://lnkd.in/dxV2C8FC](https://lnkd.in/dxV2C8FC)  
  
17\. Data Science: R Basics   
  
🔗[https://lnkd.in/dW3FDxDW](https://lnkd.in/dW3FDxDW)  
  
18\. Data Science: Probability  
  
🔗 [https://lnkd.in/dtPaSAfR](https://lnkd.in/dtPaSAfR)  
  
19\. Data Science: Visualization  
  
🔗 [https://lnkd.in/dixJWJTS](https://lnkd.in/dixJWJTS)  
  
20\. Data Science: Linear Regression  
  
🔗 [https://lnkd.in/dq4fcXD7](https://lnkd.in/dq4fcXD7)  
  
21\. Data Science: Capstone  
  
🔗 [https://lnkd.in/dDrxpmHR](https://lnkd.in/dDrxpmHR)  
  
22\. Using Python for Research  
  
🔗 [https://lnkd.in/dD6sCKqy](https://lnkd.in/dD6sCKqy)  
  
23\. Statistics and R  
  
🔗 [https://lnkd.in/dnXvB3gz](https://lnkd.in/dnXvB3gz)  
  
24\. Introduction to Bioconductor  
  
🔗[https://lnkd.in/d6D7sa8F](https://lnkd.in/d6D7sa8F)  
  
25\. Applications of TinyML  
  
🔗[ https://lnkd.in/d55rFVAF](https://lnkd.in/d55rFVAF)  
  
26\. Introduction to Digital Humanities  
  
🔗 [https://lnkd.in/dG4z\_hhP](https://lnkd.in/dG4z_hhP)  
  
27\. Data Science: Productivity Tools  
  
🔗 [https://lnkd.in/d45AZprq](https://lnkd.in/d45AZprq)  
  
28\. Data Science: Inference and Modeling  
  
🔗 [https://lnkd.in/dzhdjiCq](https://lnkd.in/dzhdjiCq)

# MIT -  Data Science

1\. Introduction to Data Science  
[https://lnkd.in/g9pUi4qh](https://lnkd.in/g9pUi4qh)  
  
2\. IBM Data Science  
[https://lnkd.in/ghznBGs6](https://lnkd.in/ghznBGs6)  
  
3\. Advanced Data Science with IBM  
[https://lnkd.in/gXVqz3ZV](https://lnkd.in/gXVqz3ZV)  
  
4\. Applied Data Science with Python  
[https://lnkd.in/gjSAFe7d](https://lnkd.in/gjSAFe7d)  
  
5\. Data Science: Foundations using R  
[https://lnkd.in/gB5h3ghH](https://lnkd.in/gB5h3ghH)  
  
6\. Learn SQL Basics for Data Science  
[https://lnkd.in/gwx3hHgB](https://lnkd.in/gwx3hHgB)  
  
7\. Data Science Fundamentals with Python and SQL  
[https://lnkd.in/gwxnGhKZ](https://lnkd.in/gwxnGhKZ)  
  
8\. Advanced Statistics for Data Science  
[https://lnkd.in/ginqyrfa](https://lnkd.in/ginqyrfa)  
  
9\. Mathematics for Machine Learning and Data Science  
[https://lnkd.in/gPc6Snzv](https://lnkd.in/gPc6Snzv)  
  
10\. Genomic Data Science  
[https://lnkd.in/gwNTraUz](https://lnkd.in/gwNTraUz)  
  
11\. Executive Data Science  
[https://lnkd.in/gP4TXK8U](https://lnkd.in/gP4TXK8U)  
  
12\. Data Science with Databricks for Data Analysts  
[https://lnkd.in/gK5WNGz4](https://lnkd.in/gK5WNGz4)

# IBM -  Data Science

<span class="break-words
      "><span dir="ltr">1. What is Data Science?  
[https://lnkd.in/g6YHb2Zx](https://lnkd.in/g6YHb2Zx)  
  
2\. Python for Data Science, AI &amp; Development  
[https://lnkd.in/gvtD8fST](https://lnkd.in/gvtD8fST)  
  
3\. Tools for Data Science  
[https://lnkd.in/gaPwdzSW](https://lnkd.in/gaPwdzSW)  
  
4\. Databases and SQL for Data Science with Python  
[https://lnkd.in/gNF3tt7W](https://lnkd.in/gNF3tt7W)  
  
5\. Machine Learning with Python  
[https://lnkd.in/gQqGxSSc](https://lnkd.in/gQqGxSSc)  
  
6\. Data Science Methodology  
[https://lnkd.in/gv-iEwx7](https://lnkd.in/gv-iEwx7)  
  
7\. Data Visualization with Python  
[https://lnkd.in/gefPVN4r](https://lnkd.in/gefPVN4r)  
  
8\. Data Analysis with Python  
[https://lnkd.in/g8C3xiYJ](https://lnkd.in/g8C3xiYJ)  
  
9\. IBM Data Science Professional Certificate  
[https://lnkd.in/g-9t4\_c7](https://lnkd.in/g-9t4_c7)  
  
10\. Python Project for Data Science  
[https://lnkd.in/gg\_36kji](https://lnkd.in/gg_36kji)  
  
11\. Exploratory Data Analysis for Machine Learning  
[https://lnkd.in/gSGx\_SVE](https://lnkd.in/gSGx_SVE)  
  
  
12\. Introduction to Data Science Specialization  
[https://lnkd.in/g-VEMct4](https://lnkd.in/g-VEMct4)  
  
13\. Excel Basics for Data Analysis  
[https://lnkd.in/gpWNE73C](https://lnkd.in/gpWNE73C)  
  
14\. Fundamentals of Scalable Data Science  
[https://lnkd.in/ghade8G8](https://lnkd.in/ghade8G8)  
  
16\. Introduction to Data Analytics  
[https://lnkd.in/gcxWBZG4](https://lnkd.in/gcxWBZG4)  
  
17\. IBM Data Analyst Professional Certificate  
[https://lnkd.in/g6Dz84eR](https://lnkd.in/g6Dz84eR)  
  
18\. Applied Data Science Capstone  
[https://lnkd.in/grFky2D4](https://lnkd.in/grFky2D4)  
  
19\. Introduction to Artificial Intelligence (AI)  
[https://lnkd.in/ghbVVMHT](https://lnkd.in/ghbVVMHT)  
  
20\. Introduction to Cybersecurity Tools &amp; Cyber Attacks  
[https://lnkd.in/gGv6-GKD](https://lnkd.in/gGv6-GKD)  
  
21\. IBM Cybersecurity Analyst Professional Certificate  
[https://lnkd.in/gh4NNgu8](https://lnkd.in/gh4NNgu8)</span></span>

# Data Engineering

<span class="break-words
      "><span dir="ltr">![](https://planforfailure.com/docs/api.gif)  
🐍 Python,  
📊 SQL,  
🛠️ MySQL,  
🌳 MongoDB,  
🔥 PySpark,  
🎈 Bash,  
🌬️ Airflow,  
☕ Kafka,  
🐙 Git,  
🐈 GitHub,  
⚙️ CICD basics,  
🏬 Data Warehousing,  
🛠️ DBT,  
🌊 Data Lakes,  
📘 DataBricks,  
☁️ Azure Databricks,  
❄️ Snowflake,  
🌪️ Apache NiFi,  
🌐 Debezium</span></span>

<span class="break-words
      "><span dir="ltr">1. Master Python:[https://lnkd.in/d7\_7sPJy](https://lnkd.in/d7_7sPJy)  
  
2\. Learn SQL: [https://lnkd.in/du4MRTxQ](https://lnkd.in/du4MRTxQ)  
  
3\. Get hands-on with MySQL: [https://lnkd.in/ds2qqZHw](https://lnkd.in/ds2qqZHw)  
  
4\. Dive into MongoDB: [https://lnkd.in/dHasTw6F](https://lnkd.in/dHasTw6F)  
  
5\. Master PySpark: [https://lnkd.in/du8rUTnj](https://lnkd.in/du8rUTnj)  
  
6\. Discover Bash, Airflow &amp; Kafka: [https://lnkd.in/df45ANxe](https://lnkd.in/df45ANxe)  
  
7\. Master Git &amp; GitHub: [https://lnkd.in/dEsF2h38](https://lnkd.in/dEsF2h38)  
  
8\. Understand CICD basics: [https://lnkd.in/d\_4WjvDc](https://lnkd.in/d_4WjvDc)  
  
9\. Decode Data Warehousing: [https://lnkd.in/dmAnYQF2](https://lnkd.in/dmAnYQF2)  
  
11\. Understand Data Lakes: [https://lnkd.in/dhKqXJmE](https://lnkd.in/dhKqXJmE)  
  
12\. Explore DataBricks: [https://lnkd.in/d4MAvUEa](https://lnkd.in/d4MAvUEa)  
  
13\. Learn Azure Databricks: [https://lnkd.in/d82RXd8T](https://lnkd.in/d82RXd8T)  
  
14\. Master Snowflake: [https://lnkd.in/dPkTAwEP](https://lnkd.in/dPkTAwEP)  
  
15\. Explore Apache NiFi: [https://lnkd.in/dHGyygfT](https://lnkd.in/dHGyygfT)</span></span>

# Fundamentals

1\. Python for Beginners

🔗 [https://lnkd.in/drQMQsBK](https://lnkd.in/drQMQsBK)

2\. Introduction to Machine Learning with Python

🔗[ https://lnkd.in/dg3Kh6ZN](https://lnkd.in/dg3Kh6ZN)

3\. Microsoft Azure AI Fundamentals

🔗[ https://lnkd.in/dM6bnkKH](https://lnkd.in/dM6bnkKH)

4\. Write Your First Code Using C#

🔗 [https://lnkd.in/dT3wXBwg](https://lnkd.in/dT3wXBwg)

5\. Get started with AI on Azure

🔗 [https://lnkd.in/d79qWhcV](https://lnkd.in/d79qWhcV)

6\. Microsoft Azure Fundamentals: Describe Cloud Concepts

🔗 [https://lnkd.in/dUhs6GMJ](https://lnkd.in/dUhs6GMJ)

7\. Introduction to GitHub

🔗 [https://lnkd.in/d6VQF2Zk](https://lnkd.in/d6VQF2Zk)

8\. Build an Early-Stage Startup

🔗 [https://lnkd.in/dZvAX-RQ](https://lnkd.in/dZvAX-RQ)

9\. Microsoft Search Fundamentals

🔗[ https://lnkd.in/d4t2uGSF](https://lnkd.in/d4t2uGSF)

10\. Get Started with Office 365

🔗 [https://lnkd.in/dYP-m2e5](https://lnkd.in/dYP-m2e5)

11\. Data Science for Beginners

🔗 [https://lnkd.in/dCuZtmeT](https://lnkd.in/dCuZtmeT)

# Introduction

1\. Introduction to Data Science  
[https://lnkd.in/dH-7aXJD](https://lnkd.in/dH-7aXJD)

2\. IBM Data Science  
[https://lnkd.in/dn7hMA4R](https://lnkd.in/dn7hMA4R)

3\. Advanced Data Science with IBM  
[https://lnkd.in/dQTakV\_4](https://lnkd.in/dQTakV_4)

4\. Applied Data Science with Python  
[https://lnkd.in/dqAe6fEn](https://lnkd.in/dqAe6fEn)

5\. Data Science: Foundations using R  
[https://lnkd.in/duJAwgcM](https://lnkd.in/duJAwgcM)

6\. Learn SQL Basics for Data Science  
[https://lnkd.in/dfn\_Xyzk](https://lnkd.in/dfn_Xyzk)

7\. Data Science Fundamentals with Python and SQL  
[https://lnkd.in/duH-vQUq](https://lnkd.in/duH-vQUq)

8\. Advanced Statistics for Data Science  
[https://lnkd.in/d9xJWa6J](https://lnkd.in/d9xJWa6J)

9\. Mathematics for Machine Learning and Data Science  
[https://lnkd.in/dBnkzjgV](https://lnkd.in/dBnkzjgV)

10\. Genomic Data Science  
[https://lnkd.in/dD8Zq6b6](https://lnkd.in/dD8Zq6b6)

11\. Executive Data Science  
[https://lnkd.in/dK6FurUN](https://lnkd.in/dK6FurUN)

12\. Data Science with Databricks for Data Analysts  
[https://lnkd.in/dsKGGj9R](https://lnkd.in/dsKGGj9R)

# Github

<span class="break-words
      "><span class="text-view-model" dir="ltr">1. Turn Data and AI algorithms into production-ready web applications with Python in no time - [https://lnkd.in/eCckCG75](https://lnkd.in/eCckCG75)  
  
2\. All Algorithms implemented in Python - [https://lnkd.in/eEU8uNkZ](https://lnkd.in/eEU8uNkZ)  
  
3\. Data science Python notebooks - [https://lnkd.in/d6rE2PNc](https://lnkd.in/d6rE2PNc)   
  
4\. Learn Ptyhon - [https://lnkd.in/e3dgvHZw](https://lnkd.in/e3dgvHZw)  
  
5\. Practice your pandas skills - [https://lnkd.in/dFuzqRKh](https://lnkd.in/dFuzqRKh)  
  
6\. 100 Days of ML Coding - [https://lnkd.in/eikbh9Pb](https://lnkd.in/eikbh9Pb)  
  
7\. Awesome Python - [https://lnkd.in/ewN\_kNPx](https://lnkd.in/ewN_kNPx)  
  
8\. Stanford's CS 229 Machine Learning - [https://lnkd.in/dtYkbVjt](https://lnkd.in/dtYkbVjt)  
  
9\. MIT Deep Learning - [https://lnkd.in/dhFcvbb5](https://lnkd.in/dhFcvbb5)  
  
10\. Data Analysis and ML Projects - [https://lnkd.in/dSAGFeZY](https://lnkd.in/dSAGFeZY)  
  
11\. Data Science related questions and answers - [https://lnkd.in/d-34wtwx](https://lnkd.in/d-34wtwx)  
  
12\. 120+ interactive Python coding interview challenges - [https://lnkd.in/eMq2zicJ](https://lnkd.in/eMq2zicJ)  
  
13\. 300 Python Interview questions with solutions - [https://lnkd.in/eKxZdc9n](https://lnkd.in/eKxZdc9n)  
  
14\. Data Science Interview Resources - [https://lnkd.in/eAKnpQm9](https://lnkd.in/eAKnpQm9)  
</span></span>

# Excel

<span class="break-words
      "><span dir="ltr">🪢Google Data Analytics:-  
🔹[https://lnkd.in/gYqKcUuq](https://lnkd.in/gYqKcUuq)  
  
&lt;&lt;&lt;&lt;&lt;Excel Courses&gt;&gt;&gt;&gt;&gt;🔥  
  
1\. Excel Skills for Business from Macquarie University  
🔹[https://lnkd.in/g7pxACQP](https://lnkd.in/g7pxACQP)  
  
2\. Everyday Excel Specialization  
🔹[https://lnkd.in/gEJa9x9d](https://lnkd.in/gEJa9x9d)  
  
3\. Excel/VBA for Creative Problem Solving  
🔹[https://lnkd.in/gpYtWuaP](https://lnkd.in/gpYtWuaP)  
  
4\. Excel Skills for Business Forecasting  
🔹[https://lnkd.in/ghCk3NQt](https://lnkd.in/ghCk3NQt)  
  
5\. Excel Skills for Data Analytics and Visualization  
🔹[https://lnkd.in/gyD6scia](https://lnkd.in/gyD6scia)  
  
6\. IBM Data Analytics with Excel and R  
🔹[https://lnkd.in/gDjsAByU](https://lnkd.in/gDjsAByU)  
  
7\. Excel to MySQL: Analytic Techniques for Business  
🔹[https://lnkd.in/g\_HQHsRh](https://lnkd.in/g_HQHsRh)  
  
8\. Excel Skills for Business Specialization  
🔹[https://lnkd.in/g7pxACQP](https://lnkd.in/g7pxACQP)  
  
9\. Excel for Beginners: Pivot Tables  
🔹[https://lnkd.in/g-jF6Rgs](https://lnkd.in/g-jF6Rgs)  
  
10\. Excel for Beginners: Introduction to Spreadsheets  
🔹[https://lnkd.in/gVVMjC64](https://lnkd.in/gVVMjC64)  
  
11\. Excel for Beginners: Advanced Functions  
🔹[https://lnkd.in/gMEmdyzR](https://lnkd.in/gMEmdyzR)  
  
12\. Using Basic Formulas and Functions in Microsoft Excel  
🔹[https://lnkd.in/g9gXCmUu](https://lnkd.in/g9gXCmUu)  
  
13\. Excel Skills for Business: Advanced  
🔹[https://lnkd.in/g54qM6qk](https://lnkd.in/g54qM6qk)  
  
14\. Using Advanced Formulas and Functions in Excel  
🔹[https://lnkd.in/gCtYEQ3B](https://lnkd.in/gCtYEQ3B)  
  
15\. Create a budget with Microsoft Excel  
🔹[https://lnkd.in/gDuAZ3yA](https://lnkd.in/gDuAZ3yA)  
  
16\. SQL  
🔹 [https://lnkd.in/dn5phvuA](https://lnkd.in/dn5phvuA)  
  
17\. C#  
🔹 [https://lnkd.in/dzew6Rz8](https://lnkd.in/dzew6Rz8)  
  
18\. SQL for Data Science  
[https://lnkd.in/dcmJr\_7N](https://lnkd.in/dcmJr_7N)  
</span></span>

# Data Engineering

1. <span class="break-words
              tvm-parent-container"><span dir="ltr">[Zach Wilson](https://www.linkedin.com/in/eczachly/)</span>   
    [https://lnkd.in/gCWMGrXE](https://lnkd.in/gCWMGrXE)  
      
    2. [Shashank Singh 🇮🇳](https://www.linkedin.com/in/shashank-singh-%F0%9F%87%AE%F0%9F%87%B3-ba4b59150/)</span>  
    [https://lnkd.in/gHbYHy-V](https://lnkd.in/gHbYHy-V)  
      
    3. [Ankit Bansal](https://www.linkedin.com/in/ankitbansal6/)   
    [https://lnkd.in/dWCVfXsA](https://lnkd.in/dWCVfXsA)  
      
    4. [Sumit Mittal](https://www.linkedin.com/in/bigdatabysumit/)   
    [https://lnkd.in/guPCM3wN](https://lnkd.in/guPCM3wN)  
      
    5. [Shashank Mishra 🇮🇳](https://www.linkedin.com/in/shashank219/)   
    [https://lnkd.in/gAzTAzaS](https://lnkd.in/gAzTAzaS)  
      
    6. [Darshil Parmar](https://www.linkedin.com/in/darshil-parmar/)   
    [https://lnkd.in/gZf6J6fm](https://lnkd.in/gZf6J6fm)  
      
    7. [Deepak Goyal](https://www.linkedin.com/in/deepak-goyal-93805a17/)  
    [https://lnkd.in/ei8RFGZQ](https://lnkd.in/ei8RFGZQ)  
      
    8. [Alex Freberg](https://www.linkedin.com/in/alex-freberg/)   
    [https://lnkd.in/gBBZZKur](https://lnkd.in/gBBZZKur)  
      
    9. [Dhaval Patel](https://www.linkedin.com/in/dhavalsays/)   
    [https://lnkd.in/ggWrgsBW](https://lnkd.in/ggWrgsBW)   
      
    10. [Benjamin Rogojan](https://www.linkedin.com/in/benjaminrogojan/)  
    [https://lnkd.in/ggXGgdPf](https://lnkd.in/ggXGgdPf)

<span class="break-words
          tvm-parent-container"><span dir="ltr">𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝗲𝘅𝗽𝗲𝗿𝘁𝘀 𝘆𝗼𝘂 𝗰𝗮𝗻 𝗳𝗼𝗹𝗹𝗼𝘄 𝗼𝗻 𝗟𝗶𝗻𝗸𝗲𝗱𝗜𝗻  
\- [Brij kishore Pandey](https://www.linkedin.com/in/brijpandeyji/)</span>  
\- [Ajay Kadiyala](https://www.linkedin.com/in/ajay026/)</span>  
\- [Munna Das](https://www.linkedin.com/in/munnadas/)  
\- [Nick Singh 📕🐒](https://www.linkedin.com/in/nick-singh-tech/)  
\- [Raghavan P](https://www.linkedin.com/in/raghavan-rp/)

# Data Science

Free Courses you will regret not taking in 2025 👇:

  
𝟭. What is Data Science: https://lnkd.in/gJvtXW8e  
𝟮. Python for DS and AI Dev: https://lnkd.in/gg3QKfHk  
𝟯. Tools for Data Science: https://lnkd.in/gRZNJBYr  
𝟰. Databases &amp; SQL for DS: https://lnkd.in/gs3PFMv6  
𝟱. Machine Learning in Python: https://lnkd.in/gxqV5hXB  
𝟲. Data Science Methodology: https://lnkd.in/ghhFzCaB  
𝟳. Data Viz with Python: https://lnkd.in/gxf8WTFj  
𝟴. Data Analysis with Python: https://lnkd.in/gyYCPUgt  
𝟵. Data Science Pro Certificate: https://lnkd.in/gy7H4\_WT  
𝟭𝟬. Projects for Data Science: https://lnkd.in/gwDUrU4i  
𝟭𝟭. EDA for Machine Learning: https://lnkd.in/g9Emaeb8  
𝟭𝟮. Intro to DS Specialization: https://lnkd.in/g5N8JBaQ  
𝟭𝟯. Excel for Data Analysis: https://lnkd.in/gDDrqTsf  
𝟭𝟰. Data Science Foundations: https://lnkd.in/g\_VWbuvK  
𝟭𝟱. Intro to Data Analytics: https://lnkd.in/gxKpsK-6  
𝟭𝟲. Data Analyst Pro : https://lnkd.in/gHwKEFZ8  
𝟭𝟳. Applied DS Capstone: https://lnkd.in/gdqrU38G  
𝟭𝟴. Introduction to AI: https://lnkd.in/gcA7gxuR  
𝟭𝟵. Intro to Cybersecurity: https://lnkd.in/g8nCwr5b  
𝟮𝟬. Cybersecurity Analyst: Pro: https://lnkd.in/gDiTsQi4  
𝟮𝟭. IBM AI Engineering: https://lnkd.in/gdiCECgX

# Google - Coursera

  
1\. Learn SQL Basics for Data Science Specialization

👉 https://lnkd.in/grqPwjRh

2\. Google Data Analytics Professional Certificate

👉 https://lnkd.in/gvNeUZGy

3\. SQL for Data Science

👉 https://lnkd.in/gT2n4VGq

4\. Databases and SQL for Data Science with Python

👉 https://lnkd.in/gvYZvSDC

5\. Introduction to Structured Query Language (SQL)

👉 https://lnkd.in/g3uDCBxH

💥 𝗙𝗥𝗘𝗘 (𝗚𝗼𝗼𝗴𝗹𝗲) 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝘆𝗼𝘂 𝘄𝗶𝗹𝗹 𝗿𝗲𝗴𝗿𝗲𝘁 𝗻𝗼𝘁 𝘁𝗮𝗸𝗶𝗻𝗴 𝗶𝗻 𝟮𝟬𝟮5.

  
1\. Google Data Analytics Professional Certificate  
🔗 https://lnkd.in/gMTNZVgp

2\. Google Project Management: Professional Certificate  
🔗https://lnkd.in/guAn9iC4

3\. Google IT Support Professional Certificate  
🔗https://lnkd.in/gH7M6uKR

4\. Foundations of Cybersecurity  
🔗https://lnkd.in/ghkYUFTa

5\. Google UX Design Professional Certificate  
🔗https://lnkd.in/gcuc3pGw

6\. Google Advanced Data Analytics Professional Certificate  
🔗https://lnkd.in/g7DhhxwE

7\. Google IT Automation with Python Professional Certificate  
🔗https://lnkd.in/gZ4nSzfd

8\. Crash Course on Python  
🔗https://lnkd.in/gZeg\_8Nx

9\. Meta Front-End Developer Professional Certificate  
🔗https://lnkd.in/g4bNBMQv

10\. Foundations of Project Management  
🔗https://lnkd.in/gDb\_fpGj

# Data Analytics

<span class="break-words
          tvm-parent-container"><span dir="ltr">1. Google Data Analytics  
🔹[https://lnkd.in/gdBBsfdr](https://lnkd.in/gdBBsfdr)  
  
2\. IBM Data Analyst  
◾[https://lnkd.in/gbUVtwji](https://lnkd.in/gbUVtwji)  
  
3\. Learn SQL Basics for Data Science  
🔹[https://lnkd.in/gnaWWpgm](https://lnkd.in/gnaWWpgm)  
  
4\. Excel for Business  
◾[https://lnkd.in/g3PV5sw2](https://lnkd.in/g3PV5sw2)  
  
5\. Python for Everybody  
🔹[https://lnkd.in/gC5eJxFp](https://lnkd.in/gC5eJxFp)  
  
6\. Data Analysis Visualization  
◾[https://lnkd.in/gTNT7dUH](https://lnkd.in/gTNT7dUH)  
  
7\. Machine Learning Specialization  
🔹[https://lnkd.in/gF6KnYmb](https://lnkd.in/gF6KnYmb)  
  
8\. Introduction to Data Science  
◾[https://lnkd.in/gPkwAWg8](https://lnkd.in/gPkwAWg8)  
  
9\. IBM Data Science Professional Certificate  
🔹[https://lnkd.in/gJ3\_Y56Z](https://lnkd.in/gJ3_Y56Z)  
  
10\. Python  
◾[https://lnkd.in/gdiA-6Hm](https://lnkd.in/gdiA-6Hm)  
  
11\. R  
🔹[https://lnkd.in/g7K\_-Ncw](https://lnkd.in/g7K_-Ncw)  
  
12\. PowerBI  
◾[https://lnkd.in/ghQ\_wiE8](https://lnkd.in/ghQ_wiE8)  
  
13\. Mathematics  
🔹[https://lnkd.in/gHxdQGcd](https://lnkd.in/gHxdQGcd)  
  
14\. Tableau  
◾[https://lnkd.in/giZRjTb3](https://lnkd.in/giZRjTb3)  
  
15\. Excel and PowerBI  
🔹[https://lnkd.in/gydKrdyg](https://lnkd.in/gydKrdyg)  
  
16\. Probability  
◾[https://lnkd.in/gY57JxdT](https://lnkd.in/gY57JxdT)  
  
17\. Statistics  
🔹[https://lnkd.in/gArjRrPw](https://lnkd.in/gArjRrPw)  
  
18\. Linear Algebra  
◾[https://lnkd.in/gg35wxUd](https://lnkd.in/gg35wxUd)  
  
19\. Deep Learning  
🔹[https://lnkd.in/gB\_-dwiD](https://lnkd.in/gB_-dwiD)  
  
20\. Data Visualization  
◾[https://lnkd.in/gRnuA-Cg](https://lnkd.in/gRnuA-Cg)  
  
21\. Microsoft Power BI Data Analyst Professional  
🔹[https://lnkd.in/ghQ\_wiE8](https://lnkd.in/ghQ_wiE8)  
  
22\. Analysis of Business Problems  
◾[https://lnkd.in/gucCyBbh](https://lnkd.in/gucCyBbh)  
  
23\. Data Analysis with R Programming  
🔹[https://lnkd.in/g7K\_-Ncw](https://lnkd.in/g7K_-Ncw)  
  
24\. Excel Skills for Business Specialization  
◾[https://lnkd.in/gws\_dJYc](https://lnkd.in/gws_dJYc)  
  
25\. SQL for Data Science  
🔹[https://lnkd.in/g2Vp4dWa](https://lnkd.in/g2Vp4dWa)  
  
26\. Databases and SQL for Data Science with Python  
◾[https://lnkd.in/g6Mx2Scs](https://lnkd.in/g6Mx2Scs)  
  
🔹27. Managerial Economics and Business Analysis Specialization  
◾[https://lnkd.in/gPRR8sDF](https://lnkd.in/gPRR8sDF)  
  
🔹28. Introduction to Business Analysis Using Spreadsheets  
◾[https://lnkd.in/g4Qw69hw](https://lnkd.in/g4Qw69hw)  
  
29\. Foundations for Big Data Analysis with SQL  
🔹[https://lnkd.in/ggVwhWZY](https://lnkd.in/ggVwhWZY)  
  
30\. Business Analysis &amp; Process Management  
◾[https://lnkd.in/gtM-aq7g](https://lnkd.in/gtM-aq7g)  
  
31\. Excel Skills for Data Analytics and Visualization  
🔹[https://lnkd.in/gq\_CJ399](https://lnkd.in/gq_CJ399)  
  
32\. IBM Data Analytics with Excel and R  
◾[https://lnkd.in/ggEZhnpp](https://lnkd.in/ggEZhnpp)  
  
33\. Business Strategy  
🔹[https://lnkd.in/gW2EiDY2](https://lnkd.in/gW2EiDY2)  
  
34\. Excel Skills for Business Forecasting  
◾[https://lnkd.in/gxzhp3BH](https://lnkd.in/gxzhp3BH)  
  
</span></span>

# 𝗚𝗶𝘁𝗵𝘂𝗯 𝗥𝗲𝗽𝗼𝘀 𝘁𝗼 𝗟𝗲𝗮𝗿𝗻 𝗣𝘆𝘁𝗵𝗼𝗻 𝗮𝗻𝗱 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲

📌 1. Learn Python 3  
By Jerry Pussinen  
[https://lnkd.in/eVbza36G](https://github.com/jerry-git/learn-python3)

📌 2. All algorithms implemented in Python  
By The Algorithms  
[https://lnkd.in/eEU8uNkZ](https://github.com/TheAlgorithms/Python)

📌 3. Data Science Resources  
By Jonathan Bower  
[https://lnkd.in/e8Qwnw\_K](https://github.com/jonathan-bower/DataScienceResources)

📌 4. Awesome Data Science  
By Fatih Aktürk, Hüseyin Mert &amp; Osman Ungur, Recep Erol  
[https://lnkd.in/e-Nj8iRJ](https://github.com/academic/awesome-datascience)

📌 5. Data Science Best Resources  
By Tirthajyoti Sarkar  
[https://lnkd.in/eEgxBKqG](https://github.com/tirthajyoti/Data-science-best-resources/blob/master/README.md)

📌 6. Data Scientist Roadmap  
By MrMimic  
[https://lnkd.in/e7fJ8p3Y](https://github.com/MrMimic/data-scientist-roadmap)

# Excel Guide

<span class="break-words
          tvm-parent-container"><span dir="ltr">Here are 10 AI tools that make Excel seem like a toy: 👇   
  
1\. SheetAI App   
\- Type your request in plain English.   
\- Automates complex tasks in minutes.   
\- Perfect for large-scale analysis.   
👉 [https://www.sheetai.app](https://www.sheetai.app)  
  
2\. Arcwise   
\- Integrates AI customized to your business.   
\- Models built directly into spreadsheets.   
\- Boosts efficiency and personalization.   
👉 [https://arcwise.app](https://arcwise.app)  
  
3\. ChatCSV (acquired by Flatfile)   
\- Ask questions directly to your CSV files.   
\- Acts like a personal data analyst.   
\- Simplifies complex queries effortlessly.   
👉 [https://www.chatcsv.co](https://www.chatcsv.co)  
  
4\. Numerous AI   
\- Integrates ChatGPT into Google Sheets.   
\- Simplifies data management and manipulation.   
\- Cost-effective and powerful.   
👉 [https://numerous.ai](https://numerous.ai)  
  
5\. Rows   
\- AI-driven data analysis, summaries, and transformations.   
\- Accelerates spreadsheet creation.   
\- Ideal for quick decision-making.   
👉 [https://rows.com/ai](https://rows.com/ai)  
  
6\. Genius Sheets   
\- Connects to internal data using natural language.   
\- Runs instant analysis like never before.   
\- Perfect for real-time insights.   
👉 [https://lnkd.in/dVtyX7xb](https://lnkd.in/dVtyX7xb)  
  
7\. Equals   
\- Start with a blank sheet and gain instant insights.   
\- Ideal for quick, AI-powered analytics.   
\- Reduces manual effort drastically.   
👉 [https://equals.com/ai](https://equals.com/ai)  
  
8\. ChartPixel   
\- Creates AI-assisted charts and slides.   
\- Turns raw data into actionable insights.   
\- Saves hours of presentation preparation.   
👉 [https://chartpixel.com](https://chartpixel.com)  
  
9\. Julius AI   
\- Chat with your data for immediate insights.   
\- Provides expert-level analytics in seconds.   
\- Easy to use and highly intuitive.   
👉 [https://julius.ai](https://julius.ai)  
  
Spreadsheets don't have to be tedious anymore.   
  
Which of these tools are you adding to your workflow? Share your thoughts below!   
  
Free Courses you will regret not taking in 2025 👇  
  
🚀7000+ free courses free access: [imp.i384100.net/vP2Ajy](http://imp.i384100.net/vP2Ajy)  
  
👉Microsoft Power BI  
[imp.i384100.net/N9Nj0b](http://imp.i384100.net/N9Nj0b)  
  
👉Deep Learning   
[imp.i384100.net/YRdZnB](http://imp.i384100.net/YRdZnB)  
  
👉Machine Learning  
[imp.i384100.net/7abYOd](http://imp.i384100.net/7abYOd)  
  
👉IBM Data Science  
[imp.i384100.net/LKD9mo](http://imp.i384100.net/LKD9mo)  
  
👉IBM Data Analysts  
[imp.i384100.net/qzgPxN](http://imp.i384100.net/qzgPxN)  
  
👉Data Analytics  
[imp.i384100.net/xLn15R](http://imp.i384100.net/xLn15R)  
  
👉Google IT support  
[imp.i384100.net/9LeKzj](http://imp.i384100.net/9LeKzj)  
  
👉Cybersecurity  
[imp.i384100.net/rag5Dy](http://imp.i384100.net/rag5Dy)  
  
👉IBM Project Manager  
[imp.i384100.net/je1qy6](http://imp.i384100.net/je1qy6)  
  
👉Google Project Management  
[imp.i384100.net/55j4Z3](http://imp.i384100.net/55j4Z3)  
  
👉AI Product Management  
[imp.i384100.net/kORxM3](http://imp.i384100.net/kORxM3)  
  
👉Meta UI/UX Design:  
[imp.i384100.net/LKD9mL](http://imp.i384100.net/LKD9mL)  
  
👉Meta Frontend Developer  
[imp.i384100.net/qzgPxj](http://imp.i384100.net/qzgPxj)  
  
👉MERN Stack Developer  
[imp.i384100.net/xLn15d](http://imp.i384100.net/xLn15d)  
  
👉Generative AI  
[imp.i384100.net/QjKknM](http://imp.i384100.net/QjKknM)  
  
👉Prompt Engineering for ChatGPT  
[imp.i384100.net/je1qyv](http://imp.i384100.net/je1qyv)  
  
Websites to Master Excel 🚀  
  
• Excel Easy  
[http://excel-easy.com](http://excel-easy.com)  
  
• Excel Campus  
[http://excelcampus.com](http://excelcampus.com)  
  
• Chandoo  
[http://chandoo.org](http://chandoo.org)  
  
• Exceljet  
[http://exceljet.net](http://exceljet.net)  
  
• Contextures  
[http://contextures.com](http://contextures.com)  
  
• MyExcelOnline  
[http://myexcelonline.com](http://myexcelonline.com)  
  
</span></span>