CourseKata’s Post

✨[Learning Progress Review of data science]📊 Hello everyone! Week 4 of our learning journey with Digital Skola was packed with valuable insights! Our team took a deep dive into Numpy, Pandas and Dataframe. We also got hands-on with manipulating arrays, creating and merging dataframe to prepare data for in-depth analysis. You can also gain knowledge about the material and how it works, which will certainly help us prepare ourselves in the field of data, especially to become a data scientist. I'm excited to share our Learning Progress Review slides, created by my team namely Cheriel Leily, Muhammad Andrean, Muhammad Faros Arkan, Raden Wisnu Murti Sulaindra, Syaiful Hidayat. #DigitalSkola #LearningProgressReview #DataScience

🌟 Learning Progress Review This week has been an exciting journey into the world of data science! I’ve delved into Numpy, exploring its powerful array operations that have greatly simplified complex mathematical computations. 📊I also learned about Introduction and Dataframe. These sessions provided me with the skills to manipulate and analyze dataframes efficiently. The ability to clean, organize, and analyze data has truly been eye-opening. 🔍 One of the highlights of this week was applying these concepts to real-world scenarios, which made the learning process both challenging and rewarding. For instance, using Numpy to handle large datasets helped me understand how crucial data preparation is for any data analysis task. A huge thank you to my team, Bald Eagle – Muhammad Faros Arkan, Savithri Maurizki Delya, Cheriel Leily, Raden Wisnu Murti Sulaindra, Syaiful Hidayat – for their collaboration on the slides, and to our amazing mentors at Digital Skola for their guidance. Your support has been invaluable! Check out my slides to see the details of what I’ve learned and feel free to connect if you have any questions or want to discuss data science! #DigitalSkola #LearningProgressReview #DataScience

I just published a new video on how to perform Principal Component Analysis (PCA) before K-means clustering in R programming: https://lnkd.in/d_2jzdWn This video showcases how PCA can be used to enhance other methods by reducing the complexity of high-dimensional data sets. It also offers a preview of the upcoming Statistics Globe online course on "Principal Component Analysis (PCA): From Theory to Application in R". This course will not only improve your proficiency in PCA but also deepen your general understanding of R, statistics, and data science. Registration ends April 2nd, so register now! More details: https://lnkd.in/eUnAqErz Looking forward to welcoming you to the course. #rstats #statistics #datascience #machinelearning #clustering

I just published a new video on how to perform Principal Component Analysis (PCA) before K-means clustering in R programming: https://lnkd.in/ewDy2u_g This video showcases how PCA can be used to enhance other methods by reducing the complexity of high-dimensional data sets. It also offers a preview of the upcoming Statistics Globe online course on "Principal Component Analysis (PCA): From Theory to Application in R". This course will not only improve your proficiency in PCA but also deepen your general understanding of R, statistics, and data science. Registration ends April 2nd, so register now! More details: https://lnkd.in/eebKdBxG Looking forward to welcoming you to the course. #rstats #statistics #datascience #machinelearning #clustering

[Learning Progress Week 8 - Data Science] Hello everyone !👋 Ahlan 🙏 Welcome back to my learning journey in Digital Skola's Data Science class! This week, we learned deeper into advanced machine learning techniques and model evaluation methods. Specifically, we focused on regression models and deployment strategies that help us implement scalable solutions. 📊🔧 🔎 Here are the key lessons from Week 8: - Regression Techniques – We explored various types of regression, including Linear Regression, Polynomial Regression, and more advanced methods like XGBoost and LightGBM. - Model Optimization – Techniques like Ridge and Lasso Regression helped us address overfitting and feature selection, ensuring robust model performance. - Model Deployment – We reinforced our understanding of deploying models through APIs, leveraging tools like Flask and Postman to ensure efficient communication between systems. 💡 This week, I learned a lot of valuable insights of both the theoretical and practical aspects of regression analysis and model deployment. Stay tuned for more updates as we continue our journey in Data Science! 🚀 #DataScience #LearningProgressReview #DigitalSkola

In the fourth week of my journey with Digital Skola, I delved into the fascinating realm of data science, focusing on essential concepts such as NumPy and arrays. This week's curriculum provided a comprehensive exploration into the definition of arrays, along with valuable insights on array manipulation. Additionally, I gained valuable knowledge about data frames, encompassing topics like functions, basic structures, and the powerful Pandas library. The week covered crucial aspects including structuring Pandas, selecting, sorting, filtering, and adding columns to data frames. Let's explore the document I shared to learn about NumPy and data frames. Join me in discovering these valuable insights and expanding our knowledge together! #digitalskola #learningprogressreview #datascience

🌟 Week 8 Learning Progress Review at Digital Skola! 🌟 This week, we explored the fascinating world of regression, learning about its types and applications. We also dove into model deployment, covering the essentials of APIs, their components, and tools like Flask and Postman. Our data science project focused on advanced data visualization techniques, including histograms, scatter plots, box plots, correlation heatmaps, pair plots, distribution plots, and QQ-plots. Check out our Week 8 slides prepared by me and the talented Integral team - rachman arifin, Nur Ainun Oktafiani, Lulu Maulatus Saidah, and Muhammad Ikhsan. Stay tuned as we continue our data science journey! 🚀📊 #DigitalSkola #LearningProgressReview #DataScience

Hi, LinkedIn People 👋 I would like to share my excitement and Insight after being part of the Fast Track Data Analytics Scholarship Batch 3 by Digital Skola During the Last Week being part of Fast Track Data Analytics Scholarship Batch 3, I learned about Dataframe ,Introduction to Google Data Studio and Data Visualization With Python, with a professional speaker, Suberlin Sinaga dan  Ari Sulistiyo Prabowo The following is a summary of the material for this week made by the Beginner 2 Master (B2M) Team, which consists of  Antika Orinda, Arya Pradipta, Annisa Fatrikha Hairani, Diajeng Esthi Anggraeni Prabowo ,and Dean Aliefgenta Ryano If you want to jump into Data Analytics, this recap would be a perfect shot for you! 💅 #DataAnalytics #BootcampDataAnalytics #SkolaClassDataAnalytics #DigitalSkola

Thrilled to have completed this course and eager to share my achievement! The knowledge gained is a stepping stone to even greater successes Unlock the power of data science with R Programming A-Z™! Dive into real exercises and elevate your skills. Let's embark on this exciting journey together. #RProgramming #DataScience #Upskill". #ProfessionalDevelopment #CourseCompletion #NewBeginnings #udemycourse

Coding with LLMs, Learning Math, Data Science Freelancing, and Other March Must-Reads https://buff.ly/3IT4a8S