Course Overview
Your journey at the Omaha Data Science Academy can go in a variety of directions. Certifications are made up of course, which can be taken on their own or as part of a certification. Certifications are designed as prerequisites and continuations of other certificates, so there are no limits to how far you can go!
Data
Visualization
FUNDAMENTALS OF
DATA SCIENCE
Business
Intelligence
Machine
Learning
DATA SCIENCE
MANAGEMENT
DS MGMT
505
Class Information
- All classes are held at 1402 Jones Street, Omaha Ne.
- All classes taught by the Omaha Data Science Academy are offered virtually and/or in person. If you choose to attend classes in person we ask that you take necessary precautions per the state guidelines.
- All in person classes will follow social distancing and masking guidelines.
- All ODSA instructors are current, practicing data scientists.
- The ODSA strives to fill its Cohorts with a students with diverse background. Not only will you build a peer group, but you will also likely learn just as much from how they solve problems as from our instructors.
- The ODSA will also connect you to data scientists in the community at large. These practicing data scientists can serve as additional peers and mentors to help with your continued growth and learning.
Omaha Data Science Academy
VIEW THE COURSE CALENDAR
COURSE CATALOG
About the Omaha Data Science Academy
ODSA History and Mission
As data scientists, the founders of the Omaha Data Science Academy (ODSA) have been part of the data science 1 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.
Why should I choose the ODSA?
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 ODSA:
1. 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.
2. 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
3. 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.
What the ODSA provides
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
- 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
2025 Calendar
Entry-Level Certificates
Fall & Winter Trimesters - 14 weeks/2 times a week
Summer Trimester - 9 weeks/3 times a week
Data Visualization Certificate (4 weeks)
- Tableau – Jan 27 - Feb 24
- Tableau – Sept 15 - Dec 17
- Power BI – TBD
Business Intelligence Certificate (12 weeks)
- Jan 27 - May 7
- Sept 15 - Dec 17
Machine Learning Certificate (12 weeks)
- Jan 27 - May 7
- Sept 15 - Dec 17
Artificial Intelligence Certificate (4 weeks)
- July 7 - July 30
Data Engineering Certificate (9 weeks)
- Mar 10 - Apr 2 (SQL101)
- July 7 - July 30 (SQL101)
- Nov 19 - Dec 17(Cloud)
Fundamentals of Data Science Certificate (2 trimesters)
- Jan 27 - May 7
- Sept 15 - Dec 17
Advanced Certificates
Data Science Management (DS Mgmt 505)
- 2 days–On-Demand
Individual Skill Modules
Fundamentals of Data Visualization (Tableau 101)
- Jan 27 - Feb 25
- Sept 15 - Dec 17
Data Manipulation and Management (SQL101)
- March 10 – April 2
- Oct 20 – Nov 12
Introduction to Python (Python 101)
- April 14 – May 7
- Nov 19 – Dec 17
Power BI (PBI 101)
- TBD
Data Engineering (DBA 101)
- TBD
Basic Model Building (Model 202)
- Jan 27 - Feb 24
- Sept 15 - Oct 18
Mathematics of Model Evaluation (Eval 202)
- March 10 – April 2
- Oct 210 – Nov 12
API & Cloud Database (Data 202)
- April 14 – May 7
- Nov 19 – Dec 17
Pricing
| Entry-Level Certificates | Price |
|
Data Visualization Certificate Business Intelligence Certificate Machine Learning Certificate Data Engineering Certificate Fundamentals of Data Science Certificate |
$1,950 $5,850 $8,550 $5,850 $14,400 |
| Advanced Certificates | Price |
| Data Science Management | $3,300 |
| Individual Skill Modules | Price |
|
How to Use Excel (Excel 101) Fundamentals of Data Visualization (Tableau 101) Fundamentals of Data Visualization - Power BI (PBI 101) Data Manipulation and Management (SQL101) Basic Model Building (Model 202) Mathematics of Model Evaluation (Eval 202) Introduction to Python (Python 101) Advanced Modeling in Python (Python 202) Data Engineering (DBA 101) API & Cloud Database (Data 202) |
$1,950 $1,950 $1,950 $1,950 $2,850 $1,950 $1,950 $1,950 $1,950 $1,950 |
Certificates
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.
Data Visualization Certification
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: $1,950.
Business Intelligence Certification
Data analysis 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: $5,850 – $3,900 plus Data Visualization Certificate Cost ($1,950)
Data Engineering Certification
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(s): 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: 72 hours. Taught 3 hours per night, 2 times per week for 12 weeks.
Cost: $5,850
Machine Learning Certification
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 Title(s): Data Scientist, 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)
- API & Cloud Database (Data 202)
- Advanced Modeling in Python (Python 202)
Duration: 96 hours. Usually taught 3 hours per night, 2x per week; 16 weeks of training.
Cost: $8,550
Fundamentals of Data Science Certification
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 Business Intelligence 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(s): 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:
- Data Visualization
- Business Intelligence
- Machine Learning/AI
Cost: There is no additional cost for this certification. The cost to attain the Data Visualization, Business Intelligence and the ML/AI certifications is: $14,400.
Data Science Management Certification
*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 Title(s): Data Science Manager, Big Data Analytics Manager
Common Job Duties:
- Those 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: $3,300
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:
- Last 3 hours per night, 2 times per week for 4 weeks (24 hours total)
- Cost $1,950 each unless otherwise stated
- May be reduced in cost using state aid
Fundamentals of Data Visualization (Tableau 101)
Fundamentals of Data Visualization (BI 101)
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.
Data Manipulation and Management (SQL 101)
How to Use Excel (Excel 101)
goal of understanding how and when to use Excel for business. This module, taken individually, does not earn a student a certificate.
Introduction to Python Programming (Python 101)
Advanced Modeling in Python (Python 202)
Data Engineering (DBA 101)
Basic Model Building (Model 202)
Mathematics of Model Evaluation (Eval 202)
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.
API & Cloud Database (Data 202)
Cloud Infrastructure and API Integration for Data Science focuses on leveraging the power of cloud platforms for scalable data science applications. It also covers the importance of APIs for data retrieval, sharing, and integration. Students will understand how to build, deploy, and manage data science pipelines in cloud environments. This module, taken individually, does not earn a student a certificate.
Data Science Management (DS Mgmt 505)
Policies
- 1.0 Program Objectives
- 2.0 Owners/Board/Advisors
- 3.0 Holidays & Weather
- 4.0 Facility & Mailing Addresses
- 5.0 Class Requirements
- 6.0 Enrollment Procedures & Entrance Requirements
- 7.0 Training & Reemployment Resources
- 8.0 Description of School's Placement Assistance
- 9.0 Attendance Policy
- 10.0 Progress & Grading Policy
- 11.0 Student Reports
- 12.0 Student Conduct
- 13.0 Readmission Policy
- 14.0 Student Probation
- 15.0 Student Records
- 16.0 Previous Credit
- 17.0 Payment & Refunds
- 18.0 Student Complaints
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
2.1 Owners
The Omaha Data Science Academy is a division of Contemporary Analysis, LLC.
2.2 2024 Advisory Board of Directors/Officers:
-
- Carrie Rosenberry, Chair –Contemporary Analysis Representative
- James Card, Vice President — Paradigm Data Scientist
- Preston Badeer, Data Science Representative — BuilderTrend Data Scientist
- Laura Paulson, Alumni Representative — US Cellular
- Donna Dostal, Donor Representative — Pottawattamie Co. Community Foundation
- Misty Mealey, Scholarship Fund Representative — Sr. Grant Writer
- Krystal Rider, At-Large Member — Director at DoSpace
2.3 2024 Officers and Instructors:
Nate Watson — Dean
- 10+ years Operational Leadership
Ida Angelma — Instructor: Python, SQL, Data Engineering
- 4 years in Data Science, Front-/Back-End Development
Tom Flaherty — Instructor: Python, Data Engineering, AI and ML
- 8 years in Data Engineering
Sam McQuistan — Instructor: SQL, Data Engineering
- 10 years in Data Science and Engineering
Charley Burtwistle — Instructor: Data Visualization with Tableau, Power BI
- 7 years in Data Visualization
3.0 Observed Holidays and Weather
The ODSA observes all federal holidays. Classes will not take place on:
-
- 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.
4.1 Facility Address
ODSA courses will be held at 1402 Jones Street, Omaha NE 68102 (in the Elevator building, unless otherwise specified).
4.2 Mailing Address
The Omaha Data Science Academy can be contacted by mail at: 505 Cornhusker Road, Suite 105-392, Bellevue, NE 68005.
5.1 Number of Student Requirements
Individual skill modules will only be offered when 3 or more students have signed up for the class.
5.2 Class Materials
Faculty will provide any handouts and lab materials (excluding computer equipment).
5.3 Equipment Requirements
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)
*The ODSA can include a laptop for an additional fee.
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
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. Training and Reemployment resources and services are available for those that qualify. (See Section 7.0).
For Payment options, see Section 17.0.
A number of services and resources are available for reemployment/career transition seekers at both the state and local levels.
To see if you qualify, go to:
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.
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 17.3 (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.
9.1 Absence Policy
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.
9.2 Tardiness policy
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).
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 12.
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).
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.
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.
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
- 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.
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.
15.1 Academic Transcript
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
- If the student graduated, withdrew, or was terminated.
15.2 Financial Transcript
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.
15.3 Access
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.
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.
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.
17.2 Company Pay
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 17.3 (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.
17.3 Refund Policy
17.3.1 Cancellation
While canceling requests are accepted at any time during a course or workshop, refund eligibility will be based on the cancellation date.
- If the cancellation date is within seventy-two (72) hours of enrollment, all monies paid shall be refunded.
- 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 9.0 Attendance Policy for additional information).
Additionally, students who are terminated from ODSA courses for misconduct will not be eligible for refunds.
Note:
- 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.
- A full refund is due to an individual whose admission is denied by the school.
- 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.
17.3.2 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.
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