CourseKata’s Post

"Thrilled to unveil my latest project: Predicting students academic performance based on study hours by The Sparks Foundation 📚🔍 Using data analysis and machine learning techniques, I delved deep into the relationship between study time and percentage scores, aiming to uncover valuable insights for optimizing learning strategies. Join me in exploring the fascinating intersection of education and data science, where every data point tells a story of potential! 💡 Your feedback and insights are greatly appreciated as I continue to refine and expand this project. Heartfelt thanks to #TheSparksFoundation for providing a platform to pursue meaningful data-driven exploration! 🌟 Let's connect to discuss how predictive analytics can empower educational practices and drive student success. #DataScience #MachineLearning #EducationAnalytics #StudentSuccess #GRIPJUN24 #PredictiveAnalytic

Hello, LinkedIn community! 🚀 Excited to Share My Latest Project: Student Placement Prediction Model! 🎓 I'm thrilled to announce the completion of an end-to-end machine learning project designed to predict student placements. This project covers the entire workflow from data preprocessing to model deployment, making it an excellent learning resource for anyone interested in machine learning and data science. 🤖 Project Highlights: 🔹 Preprocessing, EDA, and Feature Selection: Clean and explore the data to select key features. 🔹 Extract Input and Output Columns: Separate features and the target variable. 🔹 Train-Test Split: Divide the dataset for training and testing. 🔹 Scale the Values: Standardize the data for better model performance. 🔹 Train the Model: Develop and train the machine learning model. 🔹 Evaluate the Model: Assess the model using various performance metrics. 🔹 Deploy the Model: Deploy the trained model for real-time predictions. I would also like to extend my gratitude to Nitish Singh for the invaluable content he creates. His work has been a significant inspiration for this project. Feel free to check out the project on my GitHub repository and contribute if you'd like: https://lnkd.in/djZ_YCWq Looking forward to your feedback and suggestions!

Hello everyone... 👋 welcome back in this ninth week to share the data science I learned at Digital Skola . As usual there are several materials that I learned, here I describe the material I learned : 💡 Data Processing 2, this material discusses several things such as feature engineering, cycle and examples of feature engineering, Handling Text Data, CountVectorizer, and SMOTE 🔍 Classification I, this material discusses Supervised Learning, Types of supervised learning and Classification Algorithms 💻 Classification II, this material discusses Multiclass Classification and Support Vector I feel that until this ninth week, my knowledge about data science has increased. Moreover, we have entered the material about Data Processing II and Supervised learning. For friends who want to add insight into data science, you can see the files that my group and I have summarized from our learning results for eighth weeks below. Hopefully it can be useful for all of you. Keep up the spirit to keep learning 😊 #digitalskola #LearningProgressReview #datascience

Thrilled to announce that I’ve completed the Problem Solving using Data Structures course, consisting of 49 hours of in-depth learning. This course has strengthened my understanding of data structures, a fundamental aspect of efficient algorithm design and problem-solving in computer science. #DataStructures #ProblemSolving #ContinuousLearning #ComputerScience #TechSkills

My Data Science Journey 😍 After Learning Some basics Here is first project ✧ 𝙎𝙩𝙪𝙙𝙚𝙣𝙩 𝙍𝙚𝙨𝙪𝙡𝙩 𝘼𝙣𝙖𝙡𝙮𝙨𝙞𝙨 𝙒𝙞𝙩𝙝 𝙋𝙮𝙩𝙝𝙤𝙣 ✧ The dataset use from kaggle and project involves analyzing data related to student performance in Maths, Reading and Writing to identify trends, patterns, and factors Like Parent Education Parent Martial Status Gender number of study hours and more.... that influence success. This analysis can help educators and administrators understand: 𝗦𝘁𝘂𝗱𝗲𝗻𝘁 𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 :How well students are performing overall and in specific subjects. 𝘼𝙧𝙚𝙖𝙨 𝙛𝙤𝙧 𝙞𝙢𝙥𝙧𝙤𝙫𝙚𝙢𝙚𝙣𝙩: Identify areas where students need more support or where the curriculum can be improved. This Analysis Shows that parent Education has Good impact on Students Studies Score. While Parent Martial Status and no of sibling has no impact on Student Scores.

Hello everyone! 🌟 Entering the eighth week of my adventure at Digital Skola, I'm exploring the intricate realms of regression analysis and model deployment. This phase of learning has unveiled the core principles of machine learning, illuminating the process by which algorithms are trained to predict outcomes based on data. These critical competencies are the cornerstone for any aspiring data science professional, and I am enthusiastic about further developing these skills in the forthcoming weeks. Stay tuned as I share my learnings from this past week. For more details, please take a look at the slides prepared by my team. Let’s exchange ideas and continue our learning adventure!" 🚀 #DigitalSkola #LearningProgressReview #DataScience

Check out this advanced algorithms course 🤖 from CMU's David Woodruff! 🎓 Dive into big data analysis techniques like regression, subspace embeddings, and distributed computing. 💻 Don't miss this chance to level up your data skills! 📚 #Tutorial #Programming #GetVM #UniversityCourses

Hello everyone!!  In the 13th week at Digital Skola we learned some interesting material, one of which was Spark II. Spark is designed to increase efficiency and make it easier to use MapReduce. With in-memory processing and a reduced number of steps in a job, Spark can execute tasks faster. Spark's in-memory computing capabilities reduce reads and writes to disk, which significantly increases data processing speed compared to systems that rely on disk operations. This makes Spark especially effective for data analysis that requires fast response, such as interactive analysis and machine learning. Apart from that, we also learned about project six which is still related to Spark material. This project is quite complicated because it includes several materials from previous projects, including project three. Even though it is quite challenging, the material this time is very fun and in-depth. My group friends and I even made a summary, so you can read it to get a better understanding! 🚀 #StudiIndependenBersertifikat #SIBDigitalSkola #DigitalSkola #DataEngineer

And the debate over Data Science classes continues.... For now, if you are aiming for selective colleges, we recommend staying on the traditional math track, and adding Data Science as an elective, if it interests you. #collegeplanning #collegeadmissions #highschoolstudents