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DSA Education Philosophy

Simplicity

Simple yet Hard

Brevity is the soul of wit, a wise man once said. Albert Einstein said: “Genius is simplifying complex ideas, not making simple ideas complex.” Simplify, simplify and simplify more. The trick is with true understanding.

Strong evidence suggests that breaking down large complex parts into smaller, more digestible parts is the optimal strategy. We divide courses into smaller modules yet emphasize thinking holistically.

We focus on the critical fundamentals of data science, including key conceptual frameworks, complexity vs. complicated, probabilistic vs. deterministic, nonlinear thinking skills, system-level thinking skills, data interpretation skills, goal-setting skills, strategic and tactical skills, decision-making skills and scenario planning skills.

More advanced data science skills and techniques are also available, such as leadership skills and effective use of artificial intelligence technologies.

The art is knowing what conceptual framework and type of thinking is appropriate for the unique situation at hand.

Simple yet hard.

Focused yet Comprehensive

The courses focus on fundamentals yet stay cutting-edge. We've developed a proven formula to maximize value, streamline the process, focus like a laser on fundamentals, and eliminate the attractive but meaningless extras typically associated with online education.

Learn high in-demand skills and have a solid knowledge base to be competent. Have peace of mind knowing that you will graduate from each course with exceptional skills to pass certification exams and provide great value and service to an employer or client.

Time is Money

We keep it simple to focus on high-demand skills and save time, money and mental energy. Learn at your own time, pace and schedule. You are in control as each student has a unique way of learning complex material.

Courses and modules are designed by experienced applied data science professionals who have real-world experience in the field. This means you will learn from the best and gain knowledge and wisdom that you can't find in a textbook.

We ruthlessly eliminate BS so you can spend more time with family, friends and adventure to nourish the soul.

Two Sigma Problem

The "Two Sigma Problem" of education states that the "Tutoring Model" (students learn the subject with a good tutor for one to three students at a time, with testing and a feedback loop for mastery) is significantly superior to both the "Conventional Model" (students learn from a teacher in classrooms with approximately 30 other students, periodically taking assessment tests) and the "Mastery Learning Model" (conventional model plus a feedback loop so more students reach mastery).

According to a respected 1984 study by Dr. Benjamin Bloom, Professor of Education at the University of Chicago (see: http://web.mit.edu/5.95/readings/bloom-two-sigma.pdf), of the three learning models the tutoring model shifts the distribution of student performance by a little more than two standard deviations. The average student now performs in the 98% percentile relative to the conventional classroom model, and 90% of students achieve mastery of foundational skills.

DSA modified and beta tested the tutoring model to incorporate an AI Coach / Tutor 24/7 with the DSA Online Educational Platform consisting of courses / modules and tests / quizzes for instant feedback, resulting in a superior cost-effective, high-quality education.

AI Coach / Tutor 24/7

Each student has a personal AI Coach / Tutor for 24/7 hands-on learning.

DSA courses and modules are designed to be supported by a specialist AI Coach / Tutor to guide and assist you on your time and schedule. This will help solidify your understanding of the material and ensure that you can apply it to real-world problems.

Note the AI Coach / Tutor is continually improving and will adapt to each student's individual learning style in the near future.

Life is Short

Our goal is to design curriculum, set learning objectives, and evaluate student learning in a cost-effective and time-efficient manner using the DSA Online Education Platform.

We have modified Dr. Benjamin Bloom's taxonomy and mastery learning practices by incorporating AI coaches to provide students with additional support until they fully understand a concept before continuing. This allows students to achieve understanding at their own pace and time.

Our goal is to nurture data science talent and development. We believe that talent is not solely innate but can be fostered through environmental factors and effective educational practices. We aim to expand access to opportunities for all students.

Applied data science is a rapidly growing field that will innovate with new concepts, skills and techniques, especially with artificial intelligence, and therefore requires continuing education to keep members up to date. DSA will provide a comprehensive continuing education program with new courses and modules and cutting-edge education at DSA conferences world-wide.

DSA Education Philosophy

Simplicity

Simple yet Hard

Brevity is the soul of wit, a wise man once said. Albert Einstein said: “Genius is simplifying complex ideas, not making simple ideas complex.” Simplify, simplify and simplify more. The trick is with true understanding.

Strong evidence suggests that breaking down large complex parts into smaller, more digestible parts is the optimal strategy. We divide courses into smaller modules yet emphasize thinking holistically.

We focus on the critical fundamentals of data science, including key conceptual frameworks, complexity vs. complicated, probabilistic vs. deterministic, nonlinear thinking skills, system-level thinking skills, data interpretation skills, goal-setting skills, strategic and tactical skills, decision-making skills and scenario planning skills.

More advanced data science skills and techniques are also available, such as leadership skills and effective use of artificial intelligence technologies.

The art is knowing what conceptual framework and type of thinking is appropriate for the unique situation at hand.

Simple yet hard.

Focused yet Comprehensive

The courses focus on fundamentals yet stay cutting-edge. We've developed a proven formula to maximize value, streamline the process, focus like a laser on fundamentals, and eliminate the attractive but meaningless extras typically associated with online education.

Learn high in-demand skills and have a solid knowledge base to be competent. Have peace of mind knowing that you will graduate from each course with exceptional skills to pass certification exams and provide great value and service to an employer or client.

Time is Money

We keep it simple to focus on high-demand skills and save time, money and mental energy. Learn at your own time, pace and schedule. You are in control as each student has a unique way of learning complex material.

Courses and modules are designed by experienced applied data science professionals who have real-world experience in the field. This means you will learn from the best and gain knowledge and wisdom that you can't find in a textbook.

We ruthlessly eliminate BS so you can spend more time with family, friends and adventure to nourish the soul.

Two Sigma Problem

The "Two Sigma Problem" of education states that the "Tutoring Model" (students learn the subject with a good tutor for one to three students at a time, with testing and a feedback loop for mastery) is significantly superior to both the "Conventional Model" (students learn from a teacher in classrooms with approximately 30 other students, periodically taking assessment tests) and the "Mastery Learning Model" (conventional model plus a feedback loop so more students reach mastery).

According to a respected 1984 study by Dr. Benjamin Bloom, Professor of Education at the University of Chicago (see: http://web.mit.edu/5.95/readings/bloom-two-sigma.pdf), of the three learning models the tutoring model shifts the distribution of student performance by a little more than two standard deviations. The average student now performs in the 98% percentile relative to the conventional classroom model, and 90% of students achieve mastery of foundational skills.

DSA modified and beta tested the tutoring model to incorporate an AI Coach / Tutor 24/7 with the DSA Online Educational Platform consisting of courses / modules and tests / quizzes for instant feedback, resulting in a superior cost-effective, high-quality education.

AI Coach / Tutor 24/7

Each student has a personal AI Coach / Tutor for 24/7 hands-on learning.

DSA courses and modules are designed to be supported by a specialist AI Coach / Tutor to guide and assist you on your time and schedule. This will help solidify your understanding of the material and ensure that you can apply it to real-world problems.

Note the AI Coach / Tutor is continually improving and will adapt to each student's individual learning style in the near future.

Life is Short

Our goal is to design curriculum, set learning objectives, and evaluate student learning in a cost-effective and time-efficient manner using the DSA Online Education Platform.

We have modified Dr. Benjamin Bloom's taxonomy and mastery learning practices by incorporating AI coaches to provide students with additional support until they fully understand a concept before continuing. This allows students to achieve understanding at their own pace and time.

Our goal is to nurture data science talent and development. We believe that talent is not solely innate but can be fostered through environmental factors and effective educational practices. We aim to expand access to opportunities for all students.

Applied data science is a rapidly growing field that will innovate with new concepts, skills and techniques, especially with artificial intelligence, and therefore requires continuing education to keep members up to date. DSA will provide a comprehensive continuing education program with new courses and modules and cutting-edge education at DSA conferences world-wide.

Company Info

DSA

数据科学协会是一个非营利性专业协会,注册号为 82-3082527。

 

Data Science Association
P.O. Box 9670
Washington, D.C. 20016

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