Data Science Tutorial for Beginners ( Full Course ) #freeonlinecourse

Data Science Full Course tutorial (FREE online course) for beginners. Data science is considered the "sexiest job of the 21st century". You'll learn the important elements of data science. You'll be introduced to the principles, practices, and tools that make data science the powerful medium for critical insight in business and research. You'll have a solid foundation for future learning and applications in your work. With data science, you can do what you want to do, and do it better. This course covers the foundations of data science, data sourcing, coding, mathematics, and statistics. *We need your support to SUBSCRIBE / Click LIKE, SHARE if you find this video helpful (as the motivation for us to produce more FREE videos)* 💻 Course created by Barton Poulson from datalab.cc. ⭐️ Course Contents ⭐️ Part 1: Data Science: An Introduction – Foundations of Data Science (00:00:00) 1.1 Welcome (0:02) 2.1 Demand for Data Science (0:22) 2.2 The Data Science Venn Diagram (7:47) 2.3 The Data Science Pathway (14:45) 2.4 Roles in Data Science (19:55) 2.5 Teams in Data Science (22:44) 3.1 Big Data (28:33) 3.2 Coding (34:30) 3.3 Statistics (37:39) 3.4 Business Intelligence (41:06) 4.1 Do No Harm (42:44) 5.1 Methods Overview (49:22) 5.2 Sourcing Overview (52:47) 5.3 Coding Overview (54:47) 5.4 Math Overview (58:00) 5.5 Statistics Overview (1:02:00) 5.6 Machine Learning Overview (1:06:05) 6.1 Interpretability (1:08:55) 6.2 Actionable Insights (1:12:15) 6.3 Presentation Graphics (1:14:14) 6.4 Reproducible Research (1:30:20) 7.1 Next Steps (1:31:31) 1:39:46 Part 2: Data Sourcing: Foundations of Data Science (1:39:46) 1.1 Welcome 2.1 Metrics 2.2 Accuracy 2.3 Social Context of Measurement 3.1 Existing Data 3.2 APIs 3.3 Scraping 4.1 New Data 4.2 Interviews 4.3 Surveys 4.4 Card Sorting 4.5 Lab Experiments 4.6 A/B Testing 5.1 Next Steps 2:32:42 Part 3: Coding (2:32:42) 1.1 Welcome 2.1 Spreadsheets 2.2 Tableau Public 2.3 SPSS 2.4 JASP 2.5 Other Software 3.1 HTML 3.2 XML 3.3 JSON 4.1 R 4.2 Python 4.3 SQL 4.4 C, C++, & Java 4.5 Bash 5.1 Regex 6.1 Next Steps 4:01:09 Part 4: Mathematics (4:01:09) 1.1 Welcome 2.1 Elementary Algebra 2.2 Linear Algebra 2.3 Systems of Linear Equations 2.4 Calculus 2.5 Calculus & Optimization 3.1 Big O 3.2 Probability 4:44:03 Part 5: Statistics (4:44:03) 1.1 Welcome 2.1 Exploration Overview 2.2 Exploratory Graphics 2.3 Exploratory Statistics 2.4 Descriptive Statistics 3.1 Inferential Statistics 3.2 Hypothesis Testing 3.3 Estimation 4.1 Estimators 4.2 Measures of Fit 4.3 Feature Selection 4.4 Problems in Modeling 4.5 Model Validation 4.6 DIY 5.1 Next Step You may click CC (Caption / Subtitle) on the video or click Transcripts to read the scripts for better understanding. PUBLICATION PERMISSIONS: Original video was published with the Creative Commons Attribution license (reuse allowed). ------------------------------------------------------------------------------------ #datascience #Programming #learndatascience #datasciencetutorial #learnprogramming #datascienceforbeginners Java Tutorial Course https://youtu.be/soV56R0_A8I Java Spring Boot Web App Tutorial https://youtu.be/My0NgCZIB4c Python Tutorial https://youtu.be/whd7NsPPSyY SQL Tutorial https://youtu.be/P0VDmnoMGMg MongoDB Tutorial https://youtu.be/l0Wnwxk5rw8 HTML Tutorial https://youtu.be/4xgNO1RyUqA Visual Basic (VB) Tutorial https://youtu.be/Ke8sLtFi1m0 'C#' Tutorial https://youtu.be/xBqUEbbfpWw C++ Tutorial https://youtu.be/VDxamVk1mpw C++ Programming with Visual Studio Code https://youtu.be/O4vJsiyB0IM Data Science Tutorial https://youtu.be/5Vu-mGVUcS4 Machine Learning with Python https://youtu.be/GikgGSN0XGI PHP Tutorial https://www.youtube.com/watch?v=rN3whkrHeHI Visit https://thefree4u.com for quick access to various links and various tools, apps, knowledge, etc https://thefree4u.com