Linkedin - Data Science Foundations - Fundamentals (2022)

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[ TutGator.com ] Linkedin - Data Science Foundations - Fundamentals (2022)
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 01. Introduction
    • 001. Getting started.en.srt (2.3 KB)
    • 001. Getting started.mp4 (13.8 MB)
    02. What Is Data Science
    • 002. Supply and demand for data science.en.srt (6.4 KB)
    • 002. Supply and demand for data science.mp4 (39.1 MB)
    • 003. The data science Venn diagram.en.srt (7.5 KB)
    • 003. The data science Venn diagram.mp4 (39.3 MB)
    • 004. The data science pathway.en.srt (8.9 KB)
    • 004. The data science pathway.mp4 (58.4 MB)
    • 005. The CRISP-DM model in data science.en.srt (6.0 KB)
    • 005. The CRISP-DM model in data science.mp4 (35.2 MB)
    • 006. Roles and teams in data science.en.srt (7.7 KB)
    • 006. Roles and teams in data science.mp4 (38.7 MB)
    • 007. The role of questions in data science.en.srt (7.5 KB)
    • 007. The role of questions in data science.mp4 (42.1 MB)
    03. The Place of Data Science in the Data Universe
    • 008. Artificial intelligence.en.srt (13.4 KB)
    • 008. Artificial intelligence.mp4 (73.0 MB)
    • 009. Machine learning.en.srt (13.1 KB)
    • 009. Machine learning.mp4 (96.8 MB)
    • 010. Deep learning neural networks.en.srt (13.4 KB)
    • 010. Deep learning neural networks.mp4 (72.5 MB)
    • 011. Big data.en.srt (9.1 KB)
    • 011. Big data.mp4 (49.0 MB)
    • 012. Predictive analytics.en.srt (8.2 KB)
    • 012. Predictive analytics.mp4 (43.0 MB)
    • 013. Prescriptive analytics.en.srt (13.2 KB)
    • 013. Prescriptive analytics.mp4 (66.4 MB)
    • 014. Business intelligence.en.srt (7.0 KB)
    • 014. Business intelligence.mp4 (40.4 MB)
    04. Ethics and Agency
    • 015. Bias.en.srt (10.6 KB)
    • 015. Bias.mp4 (57.4 MB)
    • 016. Security.en.srt (8.8 KB)
    • 016. Security.mp4 (47.8 MB)
    • 017. Legal.en.srt (10.7 KB)
    • 017. Legal.mp4 (58.6 MB)
    • 018. Explainable AI.en.srt (16.1 KB)
    • 018. Explainable AI.mp4 (86.5 MB)
    • 019. Agency of algorithms and decision-makers.en.srt (8.6 KB)
    • 019. Agency of algorithms and decision-makers.mp4 (42.2 MB)
    05. Sources of Data
    • 020. Data preparation.en.srt (8.7 KB)
    • 020. Data preparation.mp4 (47.6 MB)
    • 021. Labeling data.en.srt (17.1 KB)
    • 021. Labeling data.mp4 (76.4 MB)
    • 022. In-house data.en.srt (9.9 KB)
    • 022. In-house data.mp4 (49.3 MB)
    • 023. Open data.en.srt (7.0 KB)
    • 023. Open data.mp4 (37.3 MB)
    • 024. APIs.en.srt (4.4 KB)
    • 024. APIs.mp4 (23.7 MB)
    • 025. Scraping data.en.srt (8.1 KB)
    • 025. Scraping data.mp4 (57.0 MB)
    • 026. Creating data.en.srt (9.7 KB)
    • 026. Creating data.mp4 (49.1 MB)
    • 027. Passive collection of training data.en.srt (6.8 KB)
    • 027. Passive collection of training data.mp4 (34.6 MB)
    • 028. Self-generated data.en.srt (5.5 KB)
    • 028. Self-generated data.mp4 (42.3 MB)
    • 029. Data vendors.en.srt (9.1 KB)
    • 029. Data vendors.mp4 (48.2 MB)
    • 030. Data ethics.en.srt (8.7 KB)
    • 030. Data ethics.mp4 (45.6 MB)
    06. Sources of Rules
    • 031. The enumeration of explicit rules.en.srt (6.6 KB)
    • 031. The enumeration of explicit rules.mp4 (35.6 MB)
    • 032. The derivation of rules from data analysis.en.srt (7.2 KB)
    • 032. The derivation of rules from data analysis.mp4 (53.6 MB)
    • 033. The generation of implicit rules.en.srt (5.8 KB)
    • 033. The generation of implicit rules.mp4 (31.2 MB)
    07. Tools for Data Science
    • 034. Applications for data analysis.en.srt (7.5 KB)
    • 034. Applications for data analysis.mp4 (42.7 MB)
    • 035. Languages for data science.en.srt (6.0 KB)
    • 035. Languages for data science.mp4 (34.4 MB)
    • 036. AutoML.en.srt (6.8 KB)
    • 036. AutoML.mp4 (37.5 MB)
    • 037. Machine learning as a service.en.srt (5.6 KB)
    • 037. Machine learning as a service.mp4 (29.3 MB)
    08. Mathematics for Data Science
    • 038. Sampling and probability.en.srt (7.9 KB)
    • 038. Sampling and probability.mp4 (47.3 MB)
    • 039. Algebra.en.srt (12.7 KB)
    • 039. Algebra.mp4 (64.1 MB)
    • 040. Calculus.en.srt (7.7 KB)
    • 040. Calculus.mp4 (44.2 MB)
    • 041. Optimization and the combinatorial explosion.en.srt (11.0 KB)
    • 041. Optimization and the combinatorial explosion.mp4 (53.6 MB)
    • 042. Bayes' theorem.en.srt (7.2 KB)
    • 042. Bayes' theorem.mp4 (38.7 MB)
    09. Unsupervised Learning
    • 043. Supervised vs. unsupervised learning.en.srt (5.9 KB)
    • 043. Supervised vs. unsupervised learning.mp4 (31.8 MB)
    • 044. Descriptive analyses.en.srt (11.9 KB)
    • 044. Descriptive analyses.mp4 (57.8 MB)
    • 045. Clustering.en.srt (10.4 KB)
    • 045. Clustering.mp4 (50.3 MB)
    • 046. Dimensionality reduction.en.srt (9.5 KB)
    • 046. Dimensionality reduction.mp4 (49.4 MB)
    • 047. Anomaly detection.en.srt (8.8 KB)
    • 047. Anomaly detection.mp4 (43.8 MB)
    10. Supervised Learning
    • 048. Supervised learning with predictive models.en.srt (13.1 KB)
    • 048. Supervised learning with predictive models.mp4 (65.2 MB)
    • 049. Time-series data.en.srt (15.4 KB)
    • 049. Time-series data.mp4 (80.5 MB)
    • 050. Classifying.en.srt (9.9 KB)
    • 050. Classifying.mp4 (48.7 MB)
    • 051. Feature selection and creation.en.srt (10.4 KB)
    • 051. Feature selection and creation.mp4 (50.9 MB)
    • 052. Aggregating models.en.srt (14.1 KB)
    • 052. Aggregating models.mp4 (74.4 MB)
    • 053. Validating models.en.srt (9.3 KB)

Description

Data Science Foundations: Fundamentals (2022)



https://TutGator.com

LinkedIn Learning
Duration: 5h 17m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 2.78 GB
Genre: eLearning | Language: English

Data science is driving a world-wide revolution that touches everything from business automation to social interaction. It’s also one of the fastest growing, most rewarding careers, employing analysts and engineers around the globe. This course provides an accessible, nontechnical overview of the field, covering the vocabulary, skills, jobs, tools, and techniques of data science. Instructor Barton Poulson defines the relationships to other data-saturated fields such as machine learning and artificial intelligence. He reviews the primary practices: gathering and analyzing data, formulating rules for classification and decision-making, and drawing actionable insights. He also discusses ethics and accountability and provides direction to learn more. By the end, you’ll see how data science can help you make better decisions, gain deeper insights, and make your work more effective and efficient.



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Linkedin - Data Science Foundations - Fundamentals (2022)

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2.8 GB
seeders:11
leechers:4
Linkedin - Data Science Foundations - Fundamentals (2022)

Torrent hash: 023E38D0A95DB810843C7ECF70329B6761DD936E