Data Science FULL Course for Beginners in 27 HOURS - 2025 Edition
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WsCube Tech is Vernacular Upskilling platform revolutionizing the way you learn & develop your career skills.🚀 We understand the challenges faced by job aspirants in our country. With limited resources and lack of top-notch skill mentorship in native language, many talented individuals miss out on global job opportunities. That's where WsCube Tech steps in.💹 🎯Our mission is clear: “To bridge the gap in India's upskilling ecosystem by providing tech-enabled & job-oriented training programs in vernacular languages.” We believe that language should never be barrier to learning anything. With WsCube Tech, you'll gain hands-on skills that make you globally competitive. Our courses are designed to prepare over 100M career aspirants for the 'Bharat' of future. 😊 👉Subscribe & join us on this transformative journey. Learn: ✅ Digital Marketing ✅ Web/App Development ✅ Cyber Security ✅ Python ✅ Data Science/Analytics ✅ Programming 📲For inquiries, call on +91 9269698122, 9024244886
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Data Science FULL Course for Beginners in 27 HOURS - 2025 Edition 🔴 To learn Data Analytics Course online with regular LIVE CLASSES, enroll now: https://www.wscubetech.com/landing-pages/online-data-analytics-course.html?utm_source=YouTube&utm_medium=June2024_13&utm_campaign=RV 00:00:00 - Data Science Full Course Intro 00:01:31 Data Science Maths in-depth 1 Introduction to Statistics • Population & Sample • Descriptive vs Inferential Statistics • Basic Statistical Measures 2 Measure of Central Tendency (Median, Mean, Mode) • Measures of Variability • Percentage, Percentiles, and Quartiles 3 Probability • Probability Distribution • Normal Distribution • Advanced Statistical Concepts 4 Covariance and Correlation • Central Limit Theorem • Hypothesis Testing 05:52:03 - Machine Learning Complete 1 Introduction to Machine Learning (ML) 2 Roadmap to Learning Machine Learning 3 Types of Data and Variables in ML 2 Data Cleaning: • Identifying and Handling Missing Values • One Hot Encoding & Dummy Variables • Label Encoding • Ordinal Encoding • Outlier Detection and Removal • Feature Scaling (Standardization and Normalization) • Handling Duplicate Data • Data Type Transformation 5 Feature Selection Techniques: • Backward Elimination (using mixed) • Forward Elimination (using mixed) 09:33:17 - Supervised Learning in ML 1 Train Test Split in Dataset 2 Regression Analysis: • Linear Regression Algorithm (Simple Linear) • Multiple Linear Regression • Polynomial Regression 3 Cost Function in Regression 4 R Squared Score & Adjusted R Squared in Regression Analysis 12:15:30 - Classification in ML 1 Classification 2 Logistic Regression: • Binary Classification (Practical) • Binary Classification with Multiple Inputs (Practical) • Binary Classification with Polynomial Inputs (Practical) • Multiclass Classification (Practical) 3 Confusion Matrix 4 Imbalanced Dataset Handling 5 Naive Bayes Algorithm 15:18:11 - Non-Linear Supervised Algorithm in ML 1 Non-Linear Supervised Algorithms: • Decision Tree (Classification) • Decision Tree (Regression) • K-Nearest Neighbors (Classification) 2 Hyperparameter Tuning 3 Cross-Validation 4 Unsupervised Learning 19:01:23 - Clustering in ML 1 Clustering 2 K-means Clustering 3 Hierarchical Clustering 4 DBSCAN Clustering Algorithm 5 Silhouette Score 20:52:57 - Association in ML 1 Association 2 Association Rule Learning 3 Apriori Algorithm 4 Frequent Pattern Growth Algorithm 22:15:34 - Ensemble Learning in ML 1 Ensemble Learning 2 Max Voting, Averaging & Weighted Average Voting • Practical Implementation for Regression • Practical Implementation for Classification 3 Bagging (with Bagging meta-estimator and Random forest) 23:25:50 - Deep Learning & AI Complete 1 Deep Learning Overview: • Introduction to Deep Learning • Neurons, Neural Networks, and Types of Deep Learning Networks 3 Perceptrons: • Single Layer Perceptron • Multilayer Perceptron (Artificial Neural Networks) 3 Training Process: • Forward Propagation and Backpropagation • Activation Functions • Loss Functions • Optimizers 4 Practical Applications WsCube Tech is a Vernacular Upskilling platform revolutionizing the way you learn and develop your career skills.🚀 WsCube Tech stands out as a leading EdTech platform, offering comprehensive education in Python, Machine Learning, and various Data Science skills. Our approach involves both online and classroom training, featuring hands-on projects delivered practically by seasoned industry experts. With WsCube Tech, you'll gain hands-on skills that make you globally competitive. Our courses are designed to prepare over 100 million career aspirants for the 'Bharat' of the future. 😊 📌 𝗩𝗼𝘁𝗲 𝗳𝗼𝗿 𝗼𝘂𝗿 𝗻𝗲𝘅𝘁 𝘃𝗶𝗱𝗲𝗼: https://bit.ly/share-topic-ideas Watch Now our Trending App Development Playlist & Videos: 👉 Learn Python Programming in One Video - https://www.youtube.com/watch?v=sCOw5y1RQpY 👉 DSA Full Course - https://www.youtube.com/watch?v=hCrO_cR7kno 👉 20 Python Projects in One Video - https://www.youtube.com/watch?v=OKuiyX5k6zg 👉 Excel Full Course for Data Analysis - https://www.youtube.com/watch?v=SA_SDo-cqpg For any queries, call us on: +91-7878985501 Connect with WsCube Tech on social media for the latest offers, promos, job vacancies, and much more: 😄 Facebook: https://www.facebook.com/wscubetech.india 🐦 Twitter: https://twitter.com/wscubetechindia 📱 Instagram: https://www.instagram.com/wscubetechindia/ 👨🏻💻 LinkedIn: https://www.linkedin.com/company/wscubetechindia/ 🔺 Youtube: http://bit.ly/wscubechannel 🌐 Website: http://wscubetech.com --------------------------------------| Thanks |--------------------------- #datascience #datasciencecourse #datascientist
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