Data science/ML/AI

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 ➖➖➖➖➖➖➖➖➖➖➖➖➖➖ 👉Join @bigdataspecialist for more👈

🔥FREE COURSE ON GENERATIVE AI🔥 Interested in learning about GENERATIVE AI?🔥 Here's a free course from Google. Link #generative ai #ml #ai ➖➖➖➖➖➖➖➖➖➖➖➖➖➖ Join @datascience_bds for more cool data science materials. *This channel belongs to @bigdataspecialist group

📊 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 ➖➖➖➖➖➖➖➖➖➖➖➖ 👉Join @bigdataspecialist for more👈

Data Science Pipeline ➖➖➖➖➖➖➖➖➖➖➖➖➖➖ Join @datascience_bds for more cool data science materials. *This channel belongs to @bigdataspecialist group

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 ➖➖➖➖➖➖➖➖➖➖➖➖➖➖ Join @datascience_bds for more cool data science materials. *This channel belongs to @bigdataspecialist group

Data Science vs ML vs Data Analytics vs Math Visualization created by our team. #datascience ➖➖➖➖➖➖➖➖➖➖➖➖➖➖ 👉Join @datascience_bds for more👈

data-science-ipython-notebooks Creator: Donne Martin Stars ⭐️: 22.6k Forked By: 7k GithubRepo: https://github.com/donnemartin/data-science-ipython-notebooks ➖➖➖➖➖➖➖➖➖➖➖➖➖➖ Join @datascience_bds for more cool repositories. *This channel belongs to @bigdataspecialist group

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 ➖➖➖➖➖➖➖➖➖➖➖➖➖➖ 👉Join @datascience_bds for more👈

Applied Data Science by Daniel Krasner 📄 141 pages 🔗 Book link #BigData  #DataScience  #MachineLearning  #Statistics ➖➖➖➖➖➖➖➖➖➖➖➖➖ Join @datascience_bds for more

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 ➖➖➖➖➖➖➖➖➖➖➖➖➖➖ 👉Join @bigdataspecialist for more👈