ODSA White Letters Long

About the Omaha Data Science Academy

As data scientists, the founders of the Omaha Data Science Academy (ODSA) have been part of the data science community since D.J. Patil and Jeff Hammerbacher coined the term in 2008. In the beginning, individuals and companies struggled; the field was so new there wasn’t structure or clear leadership around how to do projects, who should do them, how to add this capability to companies, or even why capability should be added. There was little talent and even fewer who could help companies understand how to measure talent. There were no peers to support new data scientists or mentors to lead those entering the field. Data scientists were islands in their own companies, trying to find knowledge the best they could.  

In 2016, a group of data scientists in Omaha decided to build an institution to give direction to the data science community and to help Omaha’s companies compete nationally and globally. They formed the ODSA to generate the peers, mentors, and professionals–in short, the data science community–Omaha needs. The ODSA’s two-fold mission is to make data science: 

  • Accessible: Too often, people are either unaware that data science is a viable career field or they mistakenly believe only certain people can be successful in it. This is simply not true; successful data scientists can come from all walks of life. What is true is that until now, the data science community has been small and insular, and has not reflected the explosive growth the field has experienced in the past decade. The data science community needs to diversify and grow. Many current data scientists did not come from universities (there was no degree locally until 2016), so the ODSA presents a unique opportunity for diverse people to enter a technical, high-paying career without expending copious time and resources required by traditional degree programs. 
  • Sustainable: For the data science community to succeed long term, the ODSA will ensure that: 
    • Companies with data science teams understand how to use and implement data science into their organizations successfully;
    • Individual data scientists’ training is relevant, useable from the start, and continuously developed over time; and
    • The data science community is sustained and grown through peer and mentor networks, meetups, conferences, and career development opportunities such as job boards, internships, and placement assistance. 

Only by having companies, individuals, and the wider community work together can data science become a thriving, lucrative field that will help our city compete globally. 

The ODSA’s mission to ensure data science is accessible means there is a path into the field for any interested person who is willing to put in the time and effort to train. The academy also is committed to growing the data science community within the greater Omaha metropolitan area so individuals are supported during the whole of their careers. At the OSDA:

  • Students learn from actual data science practitioners. 

The best way to learn is directly from practicing data scientists. Many times our professors have said things like, “Let me show you a model I used for a client earlier today…” The knowledge you’ll gain is relevant; our professors are working with local and national companies right now. The tools you’ll learn on are tools being used by companies in Omaha currently. This makes you instantly more qualified than those who are studying data science theories. 

  • We launch your career and help guide it over time. 

It’s not enough to gain the skills you need to land your first job as a data scientist; you also need to stay relevant and satisfied with your work to advance in your career. In short, you need a supportive data science community. OSDA helps you achieve this through:   

  • Opportunities for more training
  • Quarterly meetups
  • Yearly conference
  • An online community channel
  • Real world mentors
  • Peer support
  • We help the companies you might work for be successful in their data science endeavors.

Because the OSDA’s for-profit partner, Contemporary Analysis (CAN), helps companies build out their data science capabilities and provides the OSDA with instructors who are practicing in their field, CAN ensures the continued viability of Omaha company’s data science capabilities both now and for the future. 

The ODSA is invested in your short-term and long-term success. That’s why we provide:

  • Functional Knowledge, taught by practicing professionals, in the areas of:
    • Data Science Programming
    • Data Manipulation and Management
    • Data Visualization
    • Data Science Modeling including Machine Learning and AI
    • Data Engineering
    • Data Science Management
  • Understanding that a job in data is a continual learning process, including:
    • How to continue to learn as a data scientist
    • How to do data science when traditional knowledge doesn’t yield good results
  • Mentor Network
    • Contemporary Analysis
    • Professors
    • Presenters
    • Community-focused activities (meetups, conferences, etc.)
  • Peer Network
    • Classmates
    • Alumni Network
    • Practicing Professionals
    • Omaha Data Scientists Users Group
  • Career Guidance–while we don’t guarantee employment, we do offer:
    • Continuing Education Opportunities
    • Local Job Board Access
    • Resume and LinkedIn update assistance

Entry-Level Certificates

  • Data Visualization Certificate      
    • 4 weeks– January 24th-February 16th
    • 4 weeks– May 16th-June 13th
  • Business Intelligence Certificate    
    • 12 weeks– January 24th-April 27th
    • 12 weeks– May 16th-August 31st
  • Machine Learning/AI Certificate    
    • 12 weeks– January 24th–April 27th
    • 12 weeks– September 12th–December 21st
  • Data Engineering Certificate      
    • 8 weeks– February 28th-April 27th
    • 8 weeks– June 27th-August 31st

Advanced Certificates

  • Data Science Management (DS Mgmt 505)
    • 2 days–On-Demand

Individual Skill Modules

  • Fundamentals of Data Visualization (Tableau 101)
    • January 24th-February 16th
    • May 16th-June 13th
  • Basic Model Building (Model 202)
    • January 24th-February 16th
    • September 12-October 6th
  • How to Use Excel (Excel 101)
    • January 24th-February 16th
    • May 16th-June 13th
    • November 28th-December 21st
  • Data Manipulation and Management (SQL101)
    • February 28th-March 23rd
    • June 27th- July 25th
  • Power BI (PBI 101)
    • February 28th-March 23rd
    • June 27th- July 25th
  • Mathematics of Model Evaluation (Eval 202)
    • February 28th-March 23rd
    • October 17th-November 9th
  • Introduction to Python (Python 101)
    • April 4th-April 27th
    • August 8th-August 31st
  • Data Engineering (DBA 101)
    • April 4th-April 27th
    • August 8th-August 31st
  • Advanced Modeling in Python (Python 202)
    • April 4th-April 27th
    • November 28th-December 21st

Entry-Level Certificates Price

  • Data Visualization Certificate          $1,650
  • Business Intelligence Certificate           $4,650 
  • Machine Learning/AI Certificate         $4,650
  • Data Engineering Certificate          $3,000
  • Fundamentals of Data Science Certificate         $9,400

Advanced Certificates

  • Data Science Management         $2,500

Individual Skill Modules

  • Fundamentals of Data Visualization (Tableau 101)          $1,650
  • Basic Model Building (Model 202)         $1,650
  • How to Use Excel (Excel 101)          $1,650
  • Data Manipulation and Management (SQL101).          $1,650
  • Power BI (PBI 101).          $1,650
  • Mathematics of Model Evaluation (Eval 202).          $1,650
  • Introduction to Python (Python 101).          $1,650
  • Data Engineering (DBA 101).          $1,650
  • Advanced Modeling in Python (Python 202).          $1,650

Certificates and Courses

Job Title Readiness Certificates

The ODSA prepares a person for a specific job by teaching specific individual skill modules in combinations reflecting common duties of a specific job title. We do this by using practicing professionals who teach you the skills they use every day. Below are Job Titles and their corresponding certificates. 

A Data Visualist translates complex statistics and data so that business users can better understand them and make data-driven decisions by looking at them. 

Common Job Title(s): Data Visualist

Common Job Duties:

  • Manage datasets
  • Be proficient with data visualization software
  • Understand the data’s audience and purpose
  • Choose the right visualization
  • Make visualization easy to read

Required Completed Certifications to Enroll: 

  • None

Skill Modules learned in this Certificate: 

  • Fundamentals of data visualization (Tableau 101) or Power BI (PBI 101)

Duration: 24 hours. Taught 3 hours per night, 2 times per week for 4 weeks. 

Cost: $1,650.

Data analysis, et al. is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making.

Common Job Title(s): Data Analyst, Business Intelligence Analyst, Customer Analyst, Research Analyst, or Marketing Analyst.

Common Job Duties: 

  • Find and collect data using programming (Python or equivalent)
  • Store, clean, and prepare data using SQL
  • Analyze data for insights
  • Create data visualization 
  • Present findings to stakeholders

Required Completed Certifications to Enroll: 

  • Data Visualization

Skill Modules learned in this Certificate: 

  • Introduction to Python (Python 101)
  • Data manipulation and management (SQL101)

Duration: 72 hours. Taught 3 hours per night, 2 times per week for 14 weeks (1 week breaks between modules). 

Cost: $3,000 in addition to the Data Visualization Certificate Cost ($1,650). $4,650 Cost. 

 

A database engineer creates and manages databases for an organization. This involves designing, building, and configuring the database. This also involves monitoring security, setup and maintaining software, and products related to data movement and usage, as well as being the administer of usage rights to the database. 

Common Job Title: Data Engineer

Common Job Duties:

  • Understand and install Physical Schema designs for a given Database.
  • Database install, patching, high-availability & disaster recovery design, interaction with network and system administrators.
  • Debugging and optimization skills.
  • Extract, Transform, and Load Data

Required Completed Certifications to Enroll: 

  • None

Skill Modules learned in this Certificate:

  • Data Manipulation and Management (SQL101)
  • Data Engineering (DBA 101)

Duration: 48 hours. Taught 3 hours per night, 2 times per week for 9 weeks (1 week break between modules). 

Cost: $3,000 

 

A Data Scientist builds analytics tools that utilize a company’s data to provide proactive insights into customer acquisition, operational efficiency, and other key business performance metrics.

Common Job Titles: Data Scientists, ML and or AI Programmer/Specialist/Engineer

Common Job Duties:

  • Work with product owners, management staff, and/or customers to understand problems they are having
  • Work with data engineers, data analysts, programmers, and data visualists to help find and maintain data to be used in modeling 
  • Build data models including model selection, model interpretation, and model management
  • Present models to staff, management, and users
  • Help implement and maintain those models in the enterprise

Required Completed Certifications to Enroll: 

  • None; however, a working knowledge of business intelligence (programming and SQL) is needed. 

Skill Modules learned in this Certificate:

  • Basic Model Building (Model 202)
  • Mathematics of Model Evaluation (Eval 202)
  • Advanced Modeling in Python (Python 202)

Duration:  72 hours. Usually taught 3 hours per night, 2x per week, x 12 weeks training over 14 weeks. 

Cost: $4,700 

 

The Fundamentals of Data Science Certification Data Science is wholly different from many professions since it requires command of four distinct pillars of knowledge (Programming, Database, Data Visualization, and Machine Learning) each its own discipline. This additional certification, conferred upon students when they have completed both the BI Analyst Certificate and the ML/AI Certificate,  acknowledges the significant time and effort spent learning how these pillars of knowledge work together to solve problems only data science can solve. 

Common Job Title: Data Scientist

Common Job Duties:

A data scientist’s job is to predict business outcomes so leadership can make proactive decisions and change the outcomes to their advantage e.g., customer churn, cross-sell, up-sell, re-sell, or forecasting. They do this by:

  • Creating and managing repositories for data inside the organization
  • Manipulate that data to better analyze. 
  • Build and manage models to predict outcomes
  • Research potential issues and insight inside the data
  • Present findings to non-technical leadership and/or users about their findings
  • Implement those models/findings into the enterprise for automation and use at scale. 

The Fundamentals of Data Science Certificate is conferred upon students after having completed the following three certifications:

  • BI Analyst
  • ML/AI 

Cost:

There is no additional cost for this certification. The cost to attain both the BI Analyst and the ML/AI certification is: $9,400.

 

**This is an advanced certification for those in Data Science who are planning to or already are managing Data Scientists. 

A Data Science Manager manages the design and implementation of big data solutions for the organization. This person also oversees the team responsible for predictions, models, visualizations, APIs, and databases associated with the models.  Data Science Managers typically report to C-Suite leadership. 

Common Job Titles: Data Science Manager, Big Data Analytics Manager

Duties:

  • That of a Data Scientist plus:
    • Manage Data Science team, including staff development
    • Oversee model selection, model implementation, and management
    • Present findings to C-Level executives.

Required Completed Certifications to Enroll: 

  • Must be in the role of a Data Scientist (or equivalent) with aspirations of future management or has been awarded the Fundamentals of Data Science certification.

Skill Modules learned in this Certificate:

  • Data Science Management (DS Mgmt 505)

Duration: 16 hours. Taught as a 2-day, onsite class, or as 3 hours per night, 2 times per week for 3 weeks. 

Cost: $2,500.

Individual Skill Modules

Individual skill module combinations are what makes up job readiness certificates. An individual skill module may be taken if the student only needs a specific skill or skills, but not a certificate.  

 

Note: Students completing individual skill modules will not receive a job readiness certificate (minus Tableau 101 and Power BI 101 that do lead to a Data Visualization Cert)

 

Individual skill modules are 24 hours in length and taught 3 hours per night, 2 times per week for 4 weeks.* 

Cost per skill module (unless otherwise stated) is $1,650**.

 

*See www.canlearnsmart.com for the most up to date schedules.

 

**The cost of an individual class could be reduced using state aid.

 

See Section 6.0 for state grants and their qualifications.

In this class, students will be introduced to some of the major concepts of Data Science (Python Programming, Database Management, Modeling, and Data Visualization) and some of the tools used in the profession. The tools include a crash course in the basics of programming, data structures and object oriented design, basic web development, Jupyter Notebooks, GitHub, and web scrapers, as well as functional programming concepts and key Python libraries (Numpy and Pandas). This module, taken individually, does not earn a student a certificate. 

This class teaches a student how to store and transform data specifically to be used in modeling. Students will learn database design, SQL queries, different schemas, data cleaning techniques, and data appending. The class also will introduce a tool called Dataiku, a data platforming tool used for easier data engineering and visual/drag and drop data science. This module, taken individually, does not earn a student a certificate. 

As the skill most requested by local college professors, college students, high school teachers, and employers, the Excel Basics class starts at the beginning and takes students through major functions, pivot tables, and visualization. It is designed with a goal of understanding how and when to use Excel for business. This module, taken individually, does not earn a student a certificate. 

Data Engineering is quickly becoming a highly sought skill. A Data Scientist’s best friend, a Data Engineer not only designs and manages the data sources Data Scientists use to run their algorithms, but they also extract, transform, and load the data; manage the APIs; and are usually in charge of the data and data science toolsets. This class teaches those skills as well as how to manage data flows and work with the data team to sustain modeling in the enterprise. This module, taken individually, does not earn a student a certificate. 

Data visualization jobs have increased 1,581% since 2011, according to Forbes, proving that this one skill alone is immensely valuable in helping key business users understand data, create corporate buy-in, and make decisions from data. In this class, students will learn the fundamentals of expressing data visually. We will teach you data design and how humans digest data–specifically, the fundamentals of data visualization design and construction, as well as best practices needed to implement them. This class uses Tableau, an industry-wide benchmark for quality visualization tools. 

 

Power BI is a major tool for most Data Analysts to use in Data visualization, especially when the data needs significant preparation prior to visualization. This class will teach how to visualize data using Power BI and how to collect, arrange, and prepare data for visualization. 

Fundamentally, data science is using statistics and economic modeling to predict what is likely to happen next. This class will teach the student the fundamentals of how to build common algorithms inside of an industry-leading data science platform called Dataiku. This will include the basics of model evaluation, choosing target variables and characteristics, and basic machine learning. This module, taken individually, does not earn a student a certificate. This module, taken individually, does not earn a student a certificate. 

This class will dive into the metrics behind evaluating an analytics model’s performance using F1, Accuracy, Precision, Recall, AUC, Cost matrix, and Cumulative Lift. Students also will learn to show the steps to building, testing, evaluating, adjusting/rebuilding, re-testing, and re-evaluating a model. Finally, students will learn which model to use, avoiding the pitfalls of just using accuracy as an indicator. This module, taken individually, does not earn a student a certificate. 

Data science has gone from needing to know how to code to most modeling techniques having standardized libraries that can be pasted into a program. This means that one may do data science without understanding what the models mean or actually do. This class will drill into how to program models the traditional way. Students will use Word2Vec to scrape, debug, and enhance data science models. They also will learn how to use Python to solve other gaps such as calculations, other data manipulation, and random number population. This module, taken individually, does not earn a student a certificate. 

Data Scientists are a new type of employee and require a new type of leadership, understanding, and management. Taught in workshop format alongside the book, “Leading a Data Driven Organization – A Practical Guide to Transforming Yourself and Your Organization to Win the Data Science Revolution,” this class walks through the concepts of data science to equip students to succeed as leaders in the field.

1.0 Program Objectives

The purpose of the ODSA is to support efforts to address the tech talent shortage in the Midwest experienced by government, non-profits, startup companies, small to medium-sized businesses, and major corporations. The ODSA accomplishes this by providing job-specific training in data science led by practicing professionals, so students can gain the skills they need to secure employment and companies can fill their staffing and organizational needs.  

 

Maximum student-to-teacher ratios for each ODSA course is 15:1

2.0 Owners & Board of Directors/Officers

The Omaha Data Science Academy is a division of Contemporary Analysis, LLC.

2022 Advisory Board Members: 

  • Carrie Rosenberry–Contemporary Analysis Representative, Chair
  • Jesse Rothgeeb, Booze Allen & Hamilton–Business Representative
  • Laura Paulson, US Cellular — Alumni Representative
  • Preston Badeer, BuilderTrend–Data Scientist Representative
  • Donna Dostal, Pottawattamie Co. Community Foundation–Donor Representative
  • Nate Watson–Director
    • 9 years Operational Leadership
  • Gordon Summers–Head of Curriculum & Instructor–AI and ML Cert, DS
  •    Management, SQL, Excel, Data Engineering
    • 25 years Data Science and Engineer
  • Michael Fiedler–Instructor–Python, Excel, Data Engineering
    • 17 years Data Engineer 
  • Jeremy Bergmann–Instructor–SQL, Excel, Data Engineering, AI and ML
    • 14 years Data Science and Engineer 
  • David Krupp–Instructor–Data Visualization using Tableau, Power BI
    • 10 years Data Visualization

 

3.0 Observed Holidays and Weather

The ODSA observes all federal holidays. Classes will not take place:  

  • New Year’s Day
  • Martin Luther King, Jr. Day
  • Presidents Day
  • Memorial Day
  • Juneteenth 
  • Independence Day
  • Labor Day
  • Columbus Day
  • Veterans Day
  • Thanksgiving (Wednesday and Thursday)
  • Christmas Eve and Christmas Day
  • New Year’s Eve

Additionally, in the event of inclement weather, the ODSA will make a decision by noon on that day about class attendance based on weather forecasted and predicted road conditions. Class will be notified by email and/or phone (when available). The class may be moved online or canceled depending on weather conditions. Any canceled class will be made up during the period between modules or at a different date based on a class vote. 

4.0 Description of Facility and Equipment

ODSA courses will be held at 1905 Howard Street, Omaha NE 68102 (unless otherwise specified). Faculty will provide any handouts and lab materials (excluding computer equipment).

Operating System Requirements:

  • Microsoft® Windows 10 OR Mac OS X v10.11 (El Capitan) or later
  • Chromebook (for Intro or Foundations courses only) with minimum 4GB of RAM & 16BG SSD
  • Multicore Intel processor with 64-bit support
  • 4 GB of RAM (8 GB recommended)
  • 32 GB of available hard-disk space for installation; additional free space required during necessary program installation (cannot install on a volume that uses a case-sensitive file system or on removable flash storage devices)

Note: The ODSA can include a laptop for an additional fee. 

5.0 Enrollment procedures and entrance requirements

Students are encouraged to visit the ODSA facility prior to enrollment. However, if this is not an option, students are given the opportunity to withdraw without penalty within three days following either the regularly scheduled orientation procedures or following a tour of the school facilities and inspection of equipment.

 

To begin the enrollment process, participants must apply at:

 

www.canlearnsmart.com/enrollment-application 

 

Once an application is received, a member of the ODSA team will review the request and contact the applicant to discuss the program and answer any questions.

 

NOTE: No applicants will be allowed to join the course after the second day of any course.

 

Applicants are expected to be technologically savvy. This means they generally know how to use a computer, navigate the internet, download, install, and use programs, understand how to search for (Google, et al.) and apply how-to solutions from YouTube (or equivalent). 

 

Applicants who meet the criteria will be contacted by Nate Watson, Director of the ODSA, to complete an enrollment agreement and arrange for course payment. Financial assistance is available for those who qualify (See Section 6.0). 

 

For Payment options, see Section 16.0

6.0 Financial Assistance Programs Available.

Because Data Scientist, BI Analyst, and Data Engineer are considered an H3 career (high skills, high wage, high demand), the ODSA program qualifies for many grants and reimbursement programs. Below are some students may elect to take advantage of: 

6.1 Individual Grants

The ODSA has partnered with CRED to cover the cost of up to $1,000 of one course per year. CRED is operated by Heartland Workforce Solutions and is funded by a City of Omaha grant. This funding is to help residents in Douglas, Sarpy, and Washington counties overcome employment hurdles. **Note: If you do not reside in one of the three counties, you cannot be considered for funding. 

Apply at: https://hws-ne.org/resources/ 

The WIOA Adult/Dislocated Worker Program offers training dollars for eligible people who are laid-off, self-employed, veterans, or displaced homeworkers. Should you qualify, the WIOA Grant will cover the cost of up to one certificate and/or part of two certificates. 

Apply at: https://hws-ne.org/resources/ 

The ODSA does not currently qualify for the GI Bill. 

 

6.2 Nebraska DOL Training Assistance 

The state of Nebraska’s Department of Labor wants companies to continue to develop their workforce. For this reason, the state has an array of training assistance programs for individuals to use to better their education. Listed are but a few of the potential programs an employee could use to offset the cost of education.

 

Note: The listing of these programs does not, in any way, constitute a guarantee of employment at graduation or even assistance of employment but are simply provided as a resource of potential assistance (you and the employer must apply and be granted).

 

For the most up-to-date listing of all the Training Assistance Programs the Department of Labor has, please visit: 

https://www.dol.nebraska.gov/ReemploymentServices

Serviced by NDOL, Dynamic Workforce Solutions, or National Able (depending on where the employee lives in the state), Customized Training is a program unto which 50% of the cost of training is paid by your current employer and 50% is paid for by the service provider (NDOL, Dynamic Workforce Solutions, or National Able). 

For more information and qualifications, please email:

ndol.employerservices@nebraska.gov

The Worker Training Grant program pays up to 50% of the cost of the tuition at the ODSA. Awardees are chosen quarterly using a point system application, which includes points for: 

  • # of jobs created
  • Wage increase
  • Retention
  • Employer match (50% minimum–more points given the more you match)
  • Business size 
  • Need
  • Impact

For more information: https://www.dol.nebraska.gov/ReemploymentServices/Training/WorkerTrainingProgram

7.0 Description of school’s placement assistance

While placement is not guaranteed, the ODSA does commit to connecting students with employers and providing job placement services to the best of our abilities. This includes but is not limited to potential direct placement, connection to known associates and data science teams, invitations to various career fairs, and more. Students also can receive feedback on their resume and LinkedIn profile and be able to practice with the ODSA staff in mock interviews.

8.0 Attendance policy

Regular and punctual attendance is an integral part of the learning process. ODSA students are expected to attend scheduled courses in which they are enrolled. If a student fails to notify the course instructor of an absence, the student’s presence will be recorded as a no-show for the session. All refunds are based on the schedule detailed in Section 16.3 (Payment and Refund Policy) of the Course Catalog.

If a student falls below a 60% attendance, he or she will be dropped from the class with no refund given.

Given the complexity of the material covered in the ODSA’s courses, absences without a serious reason are highly discouraged. For students who are frequently absent, the ODSA instructors and administrators will determine the course of action, which will include a warning and may lead to termination of a student’s participation in a course. Exceptions to this policy will be considered for absence(s) that the program faculty deems justified by illness or unavoidable emergency. In the event of a prolonged illness, the student should notify program faculty as soon as possible. 

Since active participation in the academic portion of this program is mandatory, being removed from any course/workshop due to excessive absences is grounds for expulsion from the entire program without refund or recourse.

Non-attendance at required site visits, excursions, or other non-classroom activities is considered to be an absence.

Late arrivals to classes are disruptive to other students and faculty. Students who arrive to class more than 10 minutes after the class starts will receive an unexcused absence for that class period, subject to review by the instructor. Timeliness also applies to onsite visits and excursions. Site visits and excursions will depart as scheduled, with exceptions made for conditions beyond ODSA’s control (e.g., inclement weather).

9.0 Progress and Grading Policy

Students who successfully complete all of the technical learning (course/workshop tasks assigned by the instructor), demonstrate an understanding of course learning outcomes, and meet the minimum attendance requirements will receive a certificate of completion for the course.

 

Progress

Instructors will provide weekly feedback to students about their proficiency in grasping the concepts of the course, with struggling students will be given additional assistance and opportunities to succeed. There will be some time available for one-on-one instruction should the need arise.  

 

Grading

Data Scientists traditionally approach problems very differently than most other professions. They fully expect they will not have all the knowledge they need to solve the problem at hand and will need to seek additional wisdom to provide solutions. As such, the ODSA values the knowledge of knowing where to go when one runs out of knowledge as much or more as traditional “what to do” knowledge. 

This has led the OSDA to adopt a slightly different way of grading. Instead of grades, tests are pass/fail. Passing is a cumulative grade higher than 70%. In addition, students are required to attend 75% of classes as well as conduct themselves according to Section 11.

Tests are designed to ensure that students who earn OSDA certificates have a reasonable comprehension of the material they are asked to solve, while knowing where and how to find additional knowledge when what they possess is not sufficient. 

Any student who fails will be encouraged to return and retake the class. There is no charge for classes taken a second time (minus the $150 registration fee).

10.0 System of making progress reports to students

Since some ODSA training includes working with real businesses on real projects, students are expected to be respectful, professional, cooperative, and collaborative for the duration of the session.

Students who do not exhibit qualities expected of professionals in this situation will receive a verbal and written warning for the first incident. Any subsequent incidents may result in termination of course/workshop enrollment. No refund requests will be approved from students who are terminated from an ODSA course due to misconduct.

11.0​ ​Student conduct policy

Since some ODSA training includes working with real businesses on real projects, students are expected to be respectful, professional, cooperative, and collaborative for the duration of the session.

Students who do not exhibit qualities expected of professionals in this situation will receive a verbal and written warning for the first incident. Any subsequent incidents may result in termination of course/workshop enrollment. No refund requests will be approved from students who are terminated from an ODSA course due to misconduct.

12.0​ ​Readmission Policy

Students who have been expelled or voluntarily dropped from ODSA for any reason and wish to return must email Nate Watson, Director of the ODSA, at: nate@canworksmart.com. Applications are due no less than 30 days but no more than 6 months prior to the beginning of the session in which re-enrollment is desired. 

The Director will evaluate requests for readmission on the basis of the student’s written statement which must list: 

  • compelling reasons as to why they wish to return to ODSA;
  • the student indicates how and why performance will improve if readmitted; 
  • Requested readmission session

Once a decision has been made regarding the application, the student will be notified via email. Registration instructions will be sent when that information becomes available. The Director reserves the right to revoke any offer of readmission. The Director will review the progress of all students returning to the ODSA following expulsion. Continuation of enrollment is contingent upon satisfactory progress during the session the student is readmitted.

13.0 Student Probation Policy

Because of the speed and intensity of the courses, assignments outside of class are just as important as the ones inside of class. Students who fail to complete the assignments for that week will be notified via email that they are missing critical assignments. If missing assignments are not completed during a reasonable amount of time, the teacher does have the right to place the student on probation. Students on probation will not be allowed to pass their current course and will not be allowed to continue on to additional courses. The student can be removed from probation by completing the incomplete assignments at which time they will receive an email indicating they have successfully been removed from probation.

14.0 Student Record Policy

Students may request a copy of their transcript by notifying the ODSA in writing at the following email address: nate@canworksmart.com. The student will receive the transcript via email at no cost.

 

An academic transcript will be kept for all students regardless of completion. 

The academic transcript shall show:

  • Name and address of the student
  • Student’s identification number used by the school
  • Date of entry and date of exit
  • Name of the certificates/ individual skill modules pursued
  • Attendance
  • Certificates earned
  • Grades earned
  • and if the student graduated, withdrew, or was terminated.

The financial records, as dictated by the state of Nebraska, shall show: 

  • Student’s name and address
  • Student’s identification number 
  • Program of study pursued 
  • All expenses incurred
  • All payments made

The ODSA shall maintain permanent records suitable for academic and financial records for a length of no less than fifty (50) calendar years and financial records for five (5) years after the student has departed from the school.

All Certificates will have at least a signature of the ODSA director and the school seal.

 

The ODSA shall not release, transfer, disclose, or otherwise disseminate students’ records or information contained therein, unless upon the student’s written request, except to persons authorized or required to have such information by state or federal law or regulation, or pursuant to a court order.

This rule applies to all ODSA employees in their accessing and handling of student records, data or information in any form (paper, digital text, image, audio, video, microfilm, etc.) during the course of conducting ODSA business (administrative, financial, or teaching).

 

Note: Students shall have the right to review their student records, including grades, attendance, and financial records.

15.0 Credit for previous education, training, or experience

A student can petition the ODSA to take into consideration previous education, training, and/or experience for the purpose of not taking a prerequisite course. The petition may be emailed to the Director of the ODSA at nate@canworksmart.com. Permission will be granted in writing. 

16.0 Payment and Refund Policy

Any balance due after discounts or any other financial assistance is applied must be paid 50% prior to the start of the course, with the remaining 50% due within 30 days of the end of the course. No student may start another course with a balance due unless arrangements are made with the ODSA prior to the start of the next course. Monthly payments are accepted through special arrangements only and only prior to starting a course.

In the event a place of employment is covering tuition expenses, balances will be invoiced prior to the start of class. Invoiced amounts are due within 30 days of invoice unless otherwise agreed upon. 

All refund requests are subject to the policy outlined in Section 16.3 (Refund Policy) of the course catalog.

Upon satisfactory completion of all academic and skill requirements and when all financial obligations to the school have been met, the school will award a Certificate of Completion. The student and school understand that this Agreement may not be amended except in writing and signed by both parties.

Cancellation

While canceling requests are accepted at any time during a course or workshop, refund eligibility will be based on the cancellation date. 

  1. If the cancellation date is within seventy-two (72) hours of enrollment, all monies paid shall be refunded.
  2. If the cancellation date occurs after seventy-two (72) hours of enrollment, but before resident classes begin, or distance education materials are delivered, a refund shall be made of all tuition paid except a registration fee of one hundred fifty dollars ($150.00).

The cancelation date is determined by the date the student notifies the ODSA in writing at the following email address: nate@canworksmart.com. 

The cancelation and refund request email message must include the student’s name, course to cancel, and reason for cancellation. 

The cancelation process will not begin until a formal written request is received using the method described above. A student who fails to attend a course is not automatically canceled. The student is required to contact the ODSA at nate@canworksmart.com to begin the cancellation process. No shows (class absence without notice) do not count toward the cancellation date (see Attendance Policy for additional information). 

Additionally, students who are terminated from ODSA courses for misconduct will not be eligible for refunds. 

Note: 

  1. A full refund is due students whose contracted educational services are denied as a result of intentional deception, or misrepresentation of facts, or the use of advertising which is known to be false, inaccurate, or misleading.
  2. A full refund is due to an individual whose admission is denied by the school.
  3. If cancellation occurs after classes have begun, books and supplies that have been issued become the property of students and any refunds on them shall be at the discretion of the school.

Partial Refunds

The procedures for partial refund (after class has begun) is in accordance with the following schedule:

Certificates that have 2 sessions: 25% after first session

Certificates that have 3 sessions: 50% after the first session, no refund after second session

Certificates that have 4 sessions: 50% after the first session, 25% after the second session, no refund after third session

Certificates that have 5 or more sessions: 75% after first session, 50% after second session, 25% after the third session, no refund after fourth session

*Certificates that are canceled before completion but after the first course will have the discount removed for enrolling in a certificate and refunded as if courses were taken independently. 

**All refund amounts will be less the course enrollment fee of $150.00 unless meeting the requirement of full refund as stated above.

17.0 Procedure for addressing student complaints

The student may contact the ODSA’s Director regarding any concerns or complaints. Contact information is available at www.canlearnsmart.com. Complaints which cannot be resolved by direct negotiation with the school may be filed with the Program Director of Private Postsecondary Career Schools at the Nebraska Department of Education’s Program Director. Contact information is available at:  https://www.education.ne.gov/ppcs/contact-us

PROUDLY SUPPORTING OUR MILITARY MEMBERS

ODSA Military Logo

OMAHA DATA SCIENCE ACADEMY

Class Location:

2120 N. 30th Street Omaha, NE 68111

Mailing Address:
505 Cornhusker Road, Suite 105-392
Bellevue, NE 68005