BLENDED LEARNING & FLIPPED CLASSROOM

FOR DATA SCIENCE

SRAVAN ANKARAJUFOUNDER & CEO

DIVERGENCE ACADEMY

March 2nd, 2015

FLIPPING

BLENDING

SRAVAN ANKARAJU

• Technology Leader focused on Strategy & Innovation, Risk and Decision Management

• 13.5 years with Microsoft in Technology Integration consulting, Developer Support – focus on DevOps & Agile Development

• Big Picture educator – start with concepts & play to learn advanced areas. Iterate and iterate often.

• Implementer of Gamification systems in Learning/Training

• Experienced in High volume & high performance transactional systems. ,

• Data Analytics from various Fortune 100 companies

FOUNDER & CEO

AGENDA

• What is Flipped classroom & Blended learning

• Why this and Why now

• What is in the Data Science curriculum

• What is the role of Flipped classroom & Blended learning in the delivery of Data Science instruction

A learning model in which students learn content online by watching video lectures, usually at home, and homework is done in class with teachers and students discussing

and solving questions.

Teacher interaction with students is more personalized - guidance instead of lecturing.

Source: Wikipedia, Flipped Classroom

FLIPPED CLASSROOM

BLENDED LEARNINGTECHNOLOGY ENABLED ACTIVE LEARNING

Learner Centered Knowledge Centered Community Centered Assessment Centered

FLIPPED CLASSROOM

+

SCALING UP EDUCATION & KEEPING UP WITH PACE OF CHANGE

HYBRID: Traditional

Classroom & Online Learning

HANDS-ON: Practical

vocational education

PACE OF CHANGE ACCOMMODATED

WHY THIS & WHY NOW

Source: Star-Telegram; 3/27/2014

EVERY COMPANY IS NOW A TECHNOLOGY COMPANY

USE OF DATA IS PERVASIVE

190,000SHORTAGE

10,000TAKE X + AI

McKinsey report, by 2018 the US will experience a shortage of skilled data scientists

Business plans of the next 10,000 startups –Source: Wired, 10/27/2014

$1.51bTOP 7

Startup scene – DFW 51 deals, $429m in 2009; to 84 deals, $973m in 2013. Texas ranks as the #7 state in the nation for venture financing.

NEW JOBS NEW STARTUPS DFW GROWTH

Source: Tech cocktail; 2/25/2015

Oil downturn – 144,000 workers impacted. Right skill or upskill opportunities in Data science.

Source: Bloomberg

Machine joins the workforce, and algorithm gets a seat on

the board.

Source: McKinsey India. Slideshare

INDUSTRY IS CHANGING FAST

INDUSTRY & ACADEMIA ARE OFFERING NEW PROGRAMS

CORPORATE TRAINING

MOOCs

THIRD WAVE

CORE APTITUDES

AUTODIDACTS

BOOTSTRAPPING

DEMOCRATIZATION OF DATA SCIENCE

Curiosity, intellectual agility, statistical fluency, research stamina, scientific rigor, skeptical nature – that distinguish the best data scientists are widely distributed throughout the population.

-- James Kobielus, Closing the Talent Gap 17 Jan 2013

More uncredentialed, inexperienced individuals try their hands at data science, bootstrapping skills on the open-source ecosystem and using the diversity of modeling tools available. Just as data-science platforms and tools are proliferating through the magic of open source, big data’s data-scientist pool will as well.

Democratization of data science. The best data scientists will fill roles in academia, technology vendors, Wall Street, research and government.But the role of autodidacts will be bigger. AUTODIDACTS – the self-taught, uncredentialed, data-passionate people – will come to play a significant role in many organizations’ data science initiatives.

3

2

1

AUTODIDACT * BOOTSTRAPPINGRELATING TO DATA SCIENCE THROUGH VISUALIZATION

Source: Plot.ly

RELATING TO DATA SCIENCE DATA VISUALIZATIONS

MAKER PHENOMENA: DIY

TechShop is a vibrant, creative community that provides access to tools, software and space.

DATA SCIENCE

DATA SCIENCETURNING DATA INTO ACTIONS

• Data Science is the art of turning data into actions.

• Data Science tradecraft creates data products.

• Data Science capabilities can be built over time.

• Data Science is a different kind of team sport.

DATA PRODUCTPROVIDING ACTIONABLE INFORMATION

A data product provides actionable information without exposing decision makers to the underlying data or analytics.

Movie Recommendations

Weather Forecasts

Stock Market Predictions

Production Process

Improvements

Health Diagnosis Flu Trend Predictions

Targeting Advertising

FINANCIAL TRANSPARENCY

GEOGRAPHIC INFORMATION SYSTEMS (GIS)

GOVERNMENT POLICE

Source: nirvacan.com

LEARNING OUTCOMES

Source: Columbia University, Doing Data Science

DATA SCIENTISTA WORKING DEFINITION

A Data Scientist is better at statistics than a software engineer and better at software engineering than a statistician

MAKING BLENDED LEARNING POSSIBLE

EFFECTIVE LEARNING ENVIRONMENTBLENDED LEARNING ACCOMMODATE THE CHARACTERISTICS

Base knowledge on what they already know.

• Understand the broader context of “why” they are using the material. Make it practical to solve real-world problems.

• Empower students to take control of their own learning process.

Provide valuable feedback that can help both students and instructors alter the approaches to other problems & learning practices.

• Facilitate connections between learners and their larger community.

• Nudge students to apply what they learn in their classes to their everyday lives. Ex. Project capstone focused on solve a real-issue in the community

Learner Centered Knowledge Centered Community Centered Assessment Centered

WHAT DO STUDENTS LEARN

GATHER

STORAGE

VECTORIZATION

MODEL

PROCESS / PARSE

EXPLORE / TRANSFORM

TRAIN

COMMUNICATE

DATA PRODUCT

requests

BeautifulSoup4

pymongo

pandas

scikit-learn / NLTK

Flask

scrapy

Hadoop streaming w/ BeautifulSoup4

HDFS

mrjob

MLlib / pyspark

Flask

LOCALLYAT SCALE

CLASSROOM ACTIVITIES FOR ACTIVE LEARNING21st CENTURY SKILLS PROBLEM SOLVING, CRITICAL THINKING & COMMUNICATIONS

Conduct case study analyses, prepare for in-class debates, make presentations, engage in hands-on labs, create visualizations, design future project proposals, and so on.

STUDENT INFRASTRUCTURE PROVISIONING DEMO

• Private Github repository: iPython notebooks and Lectures

>> Students are given access after enrollment is completed

• Project execution on Domino Data Labs clusters

>> One project per student for the duration of the class

• Class Management & Progress tracking on edX

>> Group discussions, quizzes

METHODOLOGY

• Outcomes focused

• Project-based curriculum using real data-sets

• Guest lectures from leaders in the field

• Mock interviews and hiring preparation

• Full instructional staff + personal mentorship

GET INVOLVED

• Present a guest lecture or share a data story

• Donate datasets and propose projects

• Sponsor a scholarship

• Attend our Hiring Day

WHAT ARE WE LOOKING FOR

• Working knowledge of programming

• Background in a quantitative discipline

• Comfortable with mathematics and statistics

• Child-like curiosity

WE’RE HIRING!

• Full-time Instructors

• Teaching Assistants

• Mentors (volunteer)

THE DATA SCIENCE SERIESDIVERGENCE ACADEMY AT THE ADDISON TREEHOUSE

INTRODUCTION TO DATA SCIENCEMarch 11th, 2015; 6-8pm

PREDICT & SCORE: DEVELOPMENT TO DEPLOYMENT OF MODELSMay 13th, 2015; 6-8pm

BUILDING DATA-DRIVEN BUSINESS MODELApril 8th, 2015, 6-8pm

GET THE BIG PICTURE & THE LEARNING RESOURCES

MINING THE SOCIAL WEBMay 13th, 2015; 6-8pm

Use the 50% off discount code

1004545

THANK YOUhttp://divergence.academy