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    <title>Education for All</title>
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      <title>Learn Data Science Tutorial - Full Course for Beginners</title>
      <link>https://schoolvideos.org/watch/learn-data-science-tutorial-full-course-for-beginners_qDCUdBRUUp9C3v4.html</link>
      <pubDate>Sun, 12 Dec 2021 08:26:28 +0000</pubDate>
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      <description>Learn Data Science is this full tutorial course for absolute beginners. Data science is considered the &amp;quot;****iest job of the 21st century.&amp;quot; You&amp;#039;ll learn the important elements of data science. You&amp;#039;ll be introduced to the principles, practices, and tools that make data science the powerful medium for critical insight in business and research. You&amp;#039;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. &lt;br&gt; &lt;br&gt;💻 Course created by Barton Poulson from datalab.cc. &lt;br&gt;🔗 Check out the datalab.cc YouTube channel: &lt;a href="https://www.youtube.com/user/datalabcc" target="_blank" class="hash" rel="nofollow"&gt;https://www.youtube.com/user/datalabcc&lt;/a&gt; &lt;br&gt;🔗 Watch more free data science courses at &lt;a href="http://datalab.cc/" target="_blank" class="hash" rel="nofollow"&gt;http://datalab.cc/&lt;/a&gt; &lt;br&gt; &lt;br&gt;⭐️ Course Contents ⭐️ &lt;br&gt;⌨️ Part 1: Data Science: An Introduction: Foundations of Data Science &lt;br&gt;  - Welcome (1.1) &lt;br&gt;  - Demand for Data Science (2.1) &lt;br&gt;  - The Data Science Venn Diagram (2.2) &lt;br&gt;  - The Data Science Pathway (2.3) &lt;br&gt;  - Roles in Data Science (2.4) &lt;br&gt;  - Teams in Data Science (2.5) &lt;br&gt;  - Big Data (3.1) &lt;br&gt;  - Coding (3.2) &lt;br&gt;  - Statistics (3.3) &lt;br&gt;  - Business Intelligence (3.4) &lt;br&gt;  - Do No Harm (4.1) &lt;br&gt;  - Methods Overview (5.1) &lt;br&gt;  - Sourcing Overview (5.2) &lt;br&gt;  - Coding Overview (5.3) &lt;br&gt;  - Math Overview (5.4) &lt;br&gt;  - Statistics Overview (5.5) &lt;br&gt;  - Machine Learning Overview (5.6) &lt;br&gt;  - Interpretability (6.1) &lt;br&gt;  - Actionable Insights (6.2) &lt;br&gt;  - Presentation Graphics (6.3) &lt;br&gt;  - Reproducible Research (6.4) &lt;br&gt;  - Next Steps (7.1) &lt;br&gt;     &lt;br&gt;⌨️ Part 2: Data Sourcing: Foundations of Data Science (1:39:46) &lt;br&gt;  - Welcome (1.1)  &lt;br&gt;  - Metrics (2.1) &lt;br&gt;  - Accuracy (2.2) &lt;br&gt;  - Social Context of Measurement (2.3) &lt;br&gt;  - Existing Data (3.1) &lt;br&gt;  - APIs (3.2) &lt;br&gt;  - Scraping (3.3) &lt;br&gt;  - New Data (4.1) &lt;br&gt;  - Interviews (4.2) &lt;br&gt;  - Surveys (4.3) &lt;br&gt;  - Card Sorting (4.4) &lt;br&gt;  - Lab Experiments (4.5) &lt;br&gt;  - A/B Testing (4.6) &lt;br&gt;  - Next Steps (5.1) &lt;br&gt; &lt;br&gt;⌨️ Part 3: Coding (2:32:42) &lt;br&gt;  - Welcome (1.1) &lt;br&gt;  - Spreadsheets (2.1) &lt;br&gt;  - Tableau Public (2.2) &lt;br&gt;  - SPSS (2.3) &lt;br&gt;  - JASP (2.4) &lt;br&gt;  - Other Software (2.5) &lt;br&gt;  - HTML (3.1) &lt;br&gt;  - XML (3.2) &lt;br&gt;  - JSON (3.3) &lt;br&gt;  - R (4.1) &lt;br&gt;  - Python (4.2) &lt;br&gt;  - SQL (4.3) &lt;br&gt;  - C, C++, &amp;amp; Java (4.4) &lt;br&gt;  - Bash (4.5) &lt;br&gt;  - Regex (5.1) &lt;br&gt;  - Next Steps (6.1) &lt;br&gt;          &lt;br&gt;⌨️ Part 4: Mathematics (4:01:09) &lt;br&gt;  - Welcome (1.1) &lt;br&gt;  - Elementary Algebra (2.1) &lt;br&gt;  - Linear Algebra (2.2) &lt;br&gt;  - Systems of Linear Equations (2.3) &lt;br&gt;  - Calculus (2.4) &lt;br&gt;  - Calculus &amp;amp; Optimization (2.5) &lt;br&gt;  - Big O (3.1) &lt;br&gt;  - Probability (3.2) &lt;br&gt;           &lt;br&gt;⌨️ Part 5: Statistics (4:44:03) &lt;br&gt;  - Welcome (1.1) &lt;br&gt;  - Exploration Overview (2.1) &lt;br&gt;  - Exploratory Graphics (2.2) &lt;br&gt;  - Exploratory Statistics (2.3) &lt;br&gt;  - Descriptive Statistics (2.4) &lt;br&gt;  - Inferential Statistics (3.1) &lt;br&gt;  - Hypothesis Testing (3.2) &lt;br&gt;  - Estimation (3.3) &lt;br&gt;  - Estimators (4.1) &lt;br&gt;  - Measures of Fit (4.2) &lt;br&gt;  - Feature Selection (4.3) &lt;br&gt;  - Problems in Modeling (4.4) &lt;br&gt;  - Model Validation (4.5) &lt;br&gt;  - DIY (4.6) &lt;br&gt;  - Next Step (5.1) &lt;br&gt; &lt;br&gt;-- &lt;br&gt; &lt;br&gt;Learn to code for free and get a developer job: &lt;a href="https://www.freecodecamp.org" target="_blank" class="hash" rel="nofollow"&gt;https://www.freecodecamp.org&lt;/a&gt; &lt;br&gt; &lt;br&gt;Read hundreds of articles on programming: &lt;a href="https://www.freecodecamp.org" target="_blank" class="hash" rel="nofollow"&gt;https://www.freecodecamp.org&lt;/a&gt;/news &lt;br&gt; &lt;br&gt;And subscribe for new videos on technology every day: &lt;a href="https://youtube.com/subscription_center?add_user=freecodecamp" target="_blank" class="hash" rel="nofollow"&gt;https://youtube.com/subscripti....on_center?add_user=f&lt;/a&gt;</description>
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      <title>5 key skills you need to become a GREAT Data Analyst ~ Lessons from 15 years of analytics experience</title>
      <link>https://schoolvideos.org/watch/5-key-skills-you-need-to-become-a-great-data-analyst-lessons-from-15-years-of-analytics-experience_r9o4NXNnDsHn8gs.html</link>
      <pubDate>Sat, 04 Dec 2021 15:25:39 +0000</pubDate>
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      <description>Do you want to be a GREAT Data Analyst? &lt;br&gt; &lt;br&gt;In this video, I share what worked &amp;amp; what mistakes I made as a data analyst in my fifteen years of career in analytics. I started as a business analyst with Tata group in India and worked with many Fortune 500 clients all over the world in last 15 years in roles like DATA ANALYST, REPORTING ANALYST, INFORMATION ANALYST and DATA SCIENTIST.  &lt;br&gt; &lt;br&gt;In my recent role as a Senior HR Information Analyst, I worked with New Zealand Treasury.  &lt;br&gt; &lt;br&gt; &lt;br&gt;📄Topics in this video (click to jump around): &lt;br&gt;===================================== &lt;br&gt;0:00 - Introduction &amp;amp; about myself &lt;br&gt;0:44 - The five skills you need to be a GREAT Data Analyst &lt;br&gt;1:14 - Data Preparation Skills &lt;br&gt;3:49 - Number Crunching Skills &lt;br&gt;5:58 - Storytelling Skills &lt;br&gt;7:54 - Asking Questions &lt;br&gt;10:20 - Technology Skills &lt;br&gt;13:40 - How to get the data analyst skills? &lt;br&gt; &lt;br&gt;DOWNLOAD 5 Skills PDF 💻📕 &lt;br&gt;========================= &lt;br&gt;Go here 👉 &lt;a href="https://chandoo.org/wp/da5k" target="_blank" class="hash" rel="nofollow"&gt;https://chandoo.org/wp/da5k&lt;/a&gt; &lt;br&gt; &lt;br&gt;Watch these videos next &lt;br&gt;==================== &lt;br&gt;Data Preparation: &lt;br&gt;~~~ Getting Started with Power Query - &lt;a href="https://youtu.be/PiFAa_jjaEI" target="_blank" class="hash" rel="nofollow"&gt;https://youtu.be/PiFAa_jjaEI&lt;/a&gt; &lt;br&gt;~~~ Top 10 Quick tips to clean data in Excel - &lt;a href="https://youtu.be/SNVjndgWBlw" target="_blank" class="hash" rel="nofollow"&gt;https://youtu.be/SNVjndgWBlw&lt;/a&gt; &lt;br&gt; &lt;br&gt;Data Analysis: &lt;br&gt;~~~ Make your first 8 pivot reports in ≤10 minutes - &lt;a href="https://youtu.be/aofsdpjvK7w" target="_blank" class="hash" rel="nofollow"&gt;https://youtu.be/aofsdpjvK7w&lt;/a&gt; &lt;br&gt;~~~ Top 10 Formulas you need for data analysis - &lt;a href="https://youtu.be/Q-XGJbHG8Vo" target="_blank" class="hash" rel="nofollow"&gt;https://youtu.be/Q-XGJbHG8Vo&lt;/a&gt; &lt;br&gt; &lt;br&gt;Storytelling: &lt;br&gt;~~~ 6 Line charts you need to learn - &lt;a href="https://youtu.be/qxNZj3FEXto" target="_blank" class="hash" rel="nofollow"&gt;https://youtu.be/qxNZj3FEXto&lt;/a&gt; &lt;br&gt; &lt;br&gt;Data Analysis Playlist: &lt;br&gt;https://www.youtube.com/watch?v=gVr9f1GJdZc&amp;amp;list=PLmejDGrsgFyDAWOAnEiK0P787q3grsk9R &lt;br&gt; &lt;br&gt;Advanced Excel Skills: &lt;a href="https://chandoo.org/wp/advanced-excel-skills/" target="_blank" class="hash" rel="nofollow"&gt;https://chandoo.org/wp/advanced-excel-skills/&lt;/a&gt;</description>
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