Python Data Science Handbook

Python Data Science Handbook: full text in Jupyter Notebooks. This repository contains the entire Python Data Science Handbook, in the form of (free!) Jupyter notebooks.

Creator: Jake Vanderplas
Stars⭐️: 39k
Fork: 17.1K
Repo: https://github.com/jakevdp/PythonDataScienceHandbook

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NOC:Python for Data Science, IIT Madras

🆓 Free Online Course
💻 40 Lecture Videos
⏰ 5 Module
🏃‍♂️ Self paced
Teacher 👨‍🏫 : Prof. Ragunathan Rengasamy

🔗 https://nptel.ac.in/courses/106106212


#Data_Science #IIT
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Applied Data Science
by Daniel Krasner


📄 141 pages

🔗 Book link

#BigData  #DataScience  #MachineLearning  #Statistics
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Visualisation: visual representations of data and information

Modern society is often referred to as 'the information society' - but how can we make sense of all the information we are bombarded with? In this free course, Visualisation: visual representations of data and information, you will learn how to interpret, and in some cases create, visual representations of data and information that help us to see things in a different way.

⏰ Free Online Course
⏰ 9 Module
⏰ Duration : 8 hours
🏃‍♂️ Self paced
Offered by: openlearn

🔗 Course link

#Data #Visualization #data_science
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data-science-ipython-notebooks

Creator: Donne Martin
Stars ⭐️: 22.6k
Forked By: 7k
GithubRepo: https://github.com/donnemartin/data-science-ipython-notebooks
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Data Science vs ML vs Data Analytics vs Math

Visualization created by our team.


#datascience
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Artificial Neural Network for Regression

Rating ⭐️: 4.6 out of 5
Duration ⏰: 1hr 11min on-demand video
Students 👨‍🏫: 49,827
Created by: Hadelin de Ponteves, SuperDataScience Team, Ligency Team

🔗 Course link


#ai #ml #neural_networks #machine_learning #data_science #regression
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Data Science Pipeline

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📊 Data Scientists vs Software Engineers 🖥

🔍 Ever wondered what sets apart Data Scientists from Software Engineers? Let's dive into the key differences!

📈 Data Scientists:

💡 Their role revolves around analyzing complex data to extract valuable insights.
🔍 They focus on data analysis, modeling, and visualization to uncover patterns and trends.
🧠 Skills include statistics, machine learning, and data mining.
🔧 Tools they commonly use are Python, R, SQL, and Jupyter Notebooks.
📋 Responsibilities include data cleaning, preprocessing, and transformation.
🌐 They often possess a strong domain knowledge in a specific industry or business area.
🎯 Their goal is to extract actionable insights from data to drive decision-making.
🔄 Workflow follows CRISP-DM, a standard process for data mining.
💼 Project examples include predictive modeling and recommendation systems.
🚀 Deployment involves integrating models and insights into existing systems or presenting them in reports.
🎯 Performance evaluation focuses on metrics like accuracy, precision, recall, and F1 score.
🤝 Collaboration involves working with cross-functional teams including domain experts and stakeholders.

💻 Software Engineers:

💡 Their role centers around designing, developing, and maintaining software systems.
🔍 They focus on software design, coding, and testing to create functional and reliable solutions.
🧠 Skills include programming languages, algorithms, and databases.
🔧 Tools they commonly use are Java, C++, JavaScript, IDEs, and version control systems.
📋 Responsibilities include developing scalable software applications.
🌐 They possess general knowledge of software engineering principles.
🎯 Their goal is to develop software that meets user needs and operates flawlessly.
🔄 Workflow follows agile or waterfall software development methodologies.
💼 Project examples include web or mobile app development and system integration.
🚀 Deployment involves delivering software for end-users to interact with directly.
🎯 Performance evaluation focuses on code efficiency, reliability, and scalability.
🤝 Collaboration involves working with other software engineers and project managers.

🚀 Whether extracting insights from data or building robust software systems, both Data Scientists and Software Engineers play essential roles in the digital landscape!

🔥 Let's celebrate their unique skills and contributions to the world of technology! 💪💻


#DataScience #SoftwareEngineering #TechComparison #DigitalWorld #DataAnalysis #SoftwareDevelopment
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🔥FREE COURSE ON GENERATIVE AI🔥

Interested in learning about GENERATIVE AI?🔥

Here's a free course from Google.

Link

#generative #ai #ml #ai

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Learn ETL using SSIS

Microsoft SQL Server Integration Services (SSIS) Training

Rating ⭐️: 4.6 out 5
Students 👨‍🎓 : 62,785
Duration ⏰ : 1hr 37min on-demand video
Created by 👨‍🏫: Rakesh Gopalakrishnan

🔗 Course Link


#ETL #SSIS
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