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Data Science Full Course 2026 | Data Science Tutorial for Beginners | Data Science | Simplilearn
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Data Analysis | Learn Data Analysis | Simplilearn 🔥[2026 Updated] - Data Science Full Course 2026 | Data Science Tutorial for Beginners | Data Science | Simplilearn

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This course includes

  • 2218 hours of video
  • Certificate of completion
  • Access on mobile and TV

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🔥Data Scientist Masters Program (Discount Code - YTBE15) - https://www.simplilearn.com/big-data-and-analytics/senior-data-scientist-masters-program-training?utm_campaign=U1NX9SFkGzI&utm_medium=DescriptionFirstFold&utm_source=Youtube 🔥Microsoft Azure - Data Analyst Course - https://www.simplilearn.com/in/data-analyst-course?utm_campaign=U1NX9SFkGzI&utm_medium=DescriptionFirstFold&utm_source=Youtube 🔥Microsoft Azure - Data Analyst Course - https://www.simplilearn.com/in/data-analyst-course?utm_campaign=U1NX9SFkGzI&utm_medium=DescriptionFirstFold&utm_source=Youtube This Data Science Full Course 2026 by Simplilearn, we begin with the basics of what data science is and the role of a data scientist. You’ll learn core concepts like data acquisition, preparation, mining, model building, and statistical analysis. The tutorial covers key topics including standard deviation, distributions, Bayes theorem, and different types of machine learning—supervised, unsupervised, logistic regression, linear regression, Naive Bayes, reinforcement learning, and Markov decision processes. You’ll also explore deep learning, AI, and machine learning algorithms such as decision trees, random forests, and K-means clustering. The course then provides a roadmap to becoming a data scientist, probability and statistics foundations, and machine learning basics. Finally, we wrap up with common data science interview questions to help you prepare for career opportunities. Following are the topics covered in Data Science Full Course 2026: 00:00:00 - Introduction to Data Science Full Course 2026 00:02:10 - What is Data Science? 00:09:53 - Data Science Basics - Deep Learning - Machine Learning - Artificial Intelligence - Data Science - What does a Data Scientist Do - Data Acquisition - Data Preparation - Data Mining - Model Building - Machine Learning Algorithms - Data Analyst vs Data Scientist vs Data Engineer - Data Preparation Life-Cycle - Model Planning Life-Cycle - Statistical and Non-Statistical Analysis - Parameter and Non-Parameter Tests - Standard Deviation - Normal Distribution - Standard Normal Distribution - Z-Score - Use Case - Basics and Terminology - Binomial Distribution - Poisson Distribution - bayes Theorem - Types of Machine Learning - Supervised Machine Learning - Unsupervised Machine Learning - Linear Regression - Logistic Regression - Naive bayes - Reinforced Learning - Supervised Machine Learning vs Unsupervised Machine Learning vs Reinforced Learning - Markov's Decision Process 03:15:36 - Roadmap to Data Science 03:24:48 - Probability and Statistics 04:11:07 - Machine Learning Basics - Classification of Machine Learning - Decision Tree in Machine Learning - Random Forest Algorithm - K Means Clustering Algorithm - Naive Bayes Classifier - What is Deep Learning? 07:28:06 - Data Science Interview Questions ✅ Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH ⏩ Check out the Data Science tutorial videos: https://www.youtube.com/watch?v=X3paOmcrTjQ&list=PLEiEAq2VkUUIEQ7ENKU5Gv0HpRDtOphC6 #datascience #datasciencecourse #datascienceroadmap #datascientist #datascienceforbeginners #machinelearning #deeplearning #datasciencetools #simplilearn #2026 ✅ About Post Graduate Program In Data Science: This in-depth Data Science program is designed for working professionals, and covers job-critical topics like R, Python programming, Machine Learning techniques, NLP notions, and Data Visualization with Tableau, using an active learning model that includes live sessions from global professionals, practical labs, IBM Hackathons, and corporate ready projects Skills Covered ✅ Exploratory Data Analysis ✅ Descriptive Statistics ✅ Inferential Statistics ✅ Model Building and Finetuning ✅ Supervised and Unsupervised Learning ✅ Ensemble Learning ✅ Deep Learning ✅ Data Visualization ✅ Generative AI ✅ Prompt Engineering ✅ ChatGPT 👉 Enroll Now: https://www.simplilearn.com/ihfc-iitd-data-analytics-genai-course?utm_campaign=U1NX9SFkGzI&utm_medium=Description&utm_source=youtube

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