1. Your organization has made a significant investment to build an
Data Science Team but the team is struggling to consistently
produce data products that have a meaningful impact on the
organization. As a result the ROI on the Data Science Team in-
vestment has not met expectations. How do you jump start your
team to improve the quality and quantity of data products
they produce?
There are many components to an Data Science Team (well de-
fined, repeatable processes and methodologies, effective tools,
data science, IT and business expertise, roles, responsibilities and
leadership) that must all work together in one coordinated work-
flow to produce significant results. How do you know which data
elements or skills are missing, lacking or not being properly
integrated into the process?
Drawing on decades of real world experience producing effec-
tive predictive analytics data products, Anova Analytics has
created a training program customized for your project that can
be deployed to kick start your Data
Data Science Team
Empowerment Boot Camp
Our Instructor, Your Data Science Team, Together in the Trenches — Your Data Science
Team will develop strategies, processes and methodologies for consistently building data
products that meet your business objectives and monetize your data.
Whether you need to kick start a newly formed Data Science Team or refocus a mature team, this customized
boot camp will accelerate their path to improved productivity and increased ROI.
Predictive Analytical Model Process Flow
αηουα Analytics
Your Boot Camp
We start by customizing the program for your organization: your people, your data, your environment and your
schedule, with the objective to build your ready to deploy model that solves your business problem. We jump start
your analytics team while we work on a data product that solves an identified business problem. At the boot camp
your analytics team will work together along side an experienced mentor to build a working predictive analytical
model using R or Python. Each step of the process will be covered in depth, demonstrating best practices and equip-
ping your team with the necessary tools for each task; specifying the business objectives, retrieving, analyzing, pre-
paring and visualizing the data, creating a predictive model, validating and evaluating the model, and putting your
data product into production. At the end of this program your team has developed a well defined, repeatable, scala-
ble process for creating data products that monetize your organization’s data.
Customized for your organization - your people, your data,
your environment, your business objective on your schedule.
Matt Clark, Fortune 100 Analytics Team
“ I was able to use R for graduate school courses, but when I encountered real world problems at my job I realized
there were gaps in my R programming skills. I tried online classes but found the curriculum lacking. Acquiring a com-
prehensive methodology from experienced instructors at Anova Analytics’ boot camp gave me a much stronger
foundation to draw from and made a big difference in my productivity. “

2. Analytics
In addition to creating a useful, fully working, ready-to-deploy, data product predictive
model that monetizes your data, your team will master the following:
 Establish and reinforce repeatable and scalable processes and workflows that allow an
Data Science Team to consistently produce data products that monetize your organization’s data
 Learn a clear definition and understanding of the responsibilities and skills required for each
role on the Data Science Team and how these roles fit together in your environment to
maximize collaboration within the team and with the rest of the organization
 Institute appropriate business objectives, reasonable data goals and success criteria for your
predictive analytics data products
 Retrieve data from a variety sources, locations and formats
 Understand and describe your data from the perspective of quality, diversity and accuracy
 Use data visualization packages to discover useful patterns in your data
 Manipulate, filter and reshape massive data sets to prepare and test data for analysis and pre-
diction
 Use the appropriate best practices and methodologies for predictive modeling in order to
achieve the best results in a data model to solve a given business problem
 Increase the accuracy of your model by tuning or combining multiple models to create ensem-
ble solution
 Develop a deeper knowledge of scientific methods to train, test and measure the performance
of your models to identify the best algorithm
 Develop an appreciation for repeatable, scalable processes with the right tools and methodolo-
gies from identifying business objectives to building and testing useful predictive data product
that create incremental business value
 Discover methods and resources to research problems, expand knowledge and expertise and
get questions answered in the data science domain
 Anova Analytics’ assessment of your team’s current capabilities, skills, tools and platforms, iden-
tify gaps, and formulate recommendations for eliminating limitations
 Comprehensive Workbook including all the code snippets and exercises
 Cheat Sheets with tips for all topics
 Certificate of Completion for each team member who attended
 Post boot camp team mentoring—16 hours
 Video recordings of presentations for future training (optional)
What Your Data Science Team Will Accomplish

3. Analytics
Additional Info
Other Anova Analytics Service Offerings:
 Consulting Services for complex data science problems
 Data Science Team Staffing and Team Building
 Individual Predictive Modeling Training
 Data Science Mentoring
PREDICTIVE MODELING TRACKS
◆ Statistical Modeling ◆ Machine Learning
◆ IoT and Sensory Data ◆ Social Media and Text Mining
◆ Forecasting and Time Series ◆ Deep Learning
WHO TO CONTACT:
(for more info, to discuss setting up a tailored Data Science Team Empowerment Boot Camp)
Brandi March Mob: 678-687-9489
Email: bmarch@anovaanalytics.com

4. Analytics
Program Architects
Frank Hasbani
Anova Analytics President and Co-founder
Frank is President and Co-Founder of Anova Analytics, leading a team of data
scientists, with significant experience at delivering training and solutions for
Data Driven Decision Support at Fortune 100 companies. Graduated with dis-
tinction from the Johns Hopkins University Data Science Specialization Cer-
tificate Program. Frank is a results driven, highly skilled visionary in data
mining technology, and a thought leader with a strong reputation for integrity, innovation, empower-
ment, and collaboration with teams and clients. He has developed data products with remarkable
success in predictive and prescriptive analytics, web analytics, program execution and delivery, financial,
compliance, banking, telco, and digital media, industrial and logistical sectors.
Szwaykowska Klimka PhD
Data Scientist at RenPath
As a postdoctoral fellow at the Naval Research Laboratory she developed
expertise is in dynamical systems theory, in particular, its application to non
-linear dynamics and networked dynamical systems. Ms. Klimka’s research
focused on the emergent motion patterns of delay-coupled swarms. She
used techniques from statistical physics to investigate the bifurcation struc-
ture of emergent swarm motion patterns in different parameter regimes. She also worked on applying
techniques from dynamical systems theory to analyze collective motions of biological cells in wound
healing, and to understand the effects of cancerous states on cell dynamical properties. Additional
areas of expertise include stochastic control, error modelling, and underwater robotics.
Mark A. Jack PhD
Senior Advisor to Anova Analytics,
Faculty Member Florida A&M University,
HPC, Pattern Recognition, Linear & Parallel Computing
Mark Jack is a theoretical physicist with expertise in computational modeling
of quantum systems and high-performance computing. Mark is a faculty
member at Florida A&M University Physics Department in Tallahassee, FL and
serves as senior advisor to Anova Analytics. As a postdoctoral researcher at
the University of California Los Angeles Neurobiology Department he worked on analyzing electrical
spike train statistics in retinal ganglion cells of mice using Bayes information theory and pattern recog-
nition techniques (k-means clustering). Mark earned his PhD in physics (dr. rer. nat.) at the Humboldt
University Berlin in Germany and is currently completing the Johns Hopkins University certificate in
Data Science Specialization (Sept 2016).