From day one, our students are fully immersed in real-world career roles, performing authentic tasks in pursuit of meaningful goals and producing the same work that professionals produce.
Supported by an experienced mentor, they receive coaching and feedback, helping students to revise their work and improve their mastery of the underlying knowledge and skills.
Along the way, we provide advice, resources, and stories from industry insiders who have actually been there.
YOU WON'T SPEND ANY TIME IN A CLASSROOM
WHEN YOU'RE DONE, YOU'LL GET A JOB*
The programs are unique in that we teach the skills needed to perform the job from day one.
We call our mentored courses "Deep Dives" because from the very first day, our students dive in to an authentic role in a real-world scenario with all the complex challenges of the programs.
Our programs center around a rich, engaging story where students are given a realistic workplace role, work to achieve real goals, overcome real challenges, and explore the opportunity make real mistakes and learn from them in a safe environment.
Along the way, your mentor provides resources, tools, and constructive, critical input on your work when you need it.
There are no lectures, there are no grades, and there are no tests.
We believe real learning comes from having an authentic, memorable experience.
"Real thinking never starts until the learner fails, [but] we punish students with bad grades when they offer the wrong answers on tests. Negative consequences give failure a bad name. For real learning to take place, there must be failure."
- Roger Schank
Led by artificial intelligence visionary Dr. Roger Schank, our team of experienced instructional design and facilitation experts have delivered education solutions to Fortune 500 companies, government agencies, and post-secondary schools for over three decades.
After 35 years as a professor at Stanford and Yale, Schank became frustrated at educational institutions that fail to produce graduates with real skills that they can use to get a job. [this points to Roger's blog and a lengthy article on the subject] Out of these frustrations, we built Schank Academy for you— the individual— to thrive.
The important thing is not to stop questioning. Curiosity has its own reason for existence. One cannot help but be in awe when he contemplates the mysteries of eternity, of life, of the marvelous structure of reality. It is enough if one tries merely to comprehend a little of this mystery each day. Albert Einstein
Do you like building things? Do you like using apps and web sites but keep wanting to change them to work better? Do you like to experiment? You may not have a technical background, be a programmer, or know much about the web, but you are willing to work hard and to learn as you go. If this description fits you, the Software Development program may be for you.
This immersive online program will teach you front-end and full-stack software development. If you're a self-starter looking to dive into one of the fastest-growing careers out there, this program will teach you the skills that will guarantee you a job.
In this course, you are an independent contractor who develops custom websites for small organizations. The Northside Youth Soccer League (NYSL) has hired you to develop a website for their soccer teams. You will work on this website on your own and will learn to use modern HTML and CSS to produce an attractive, informative multi-page website based on the client's requirements.
In this course, you are a developer at Code of the Web, a small software shop that creates custom JavaScript-based web applications. Transparent Government in Fact, a non-partisan non-profit organization working to increase the public's involvement in government, has hired you to develop a Congressional tracking web site for them. You will work on this web application using modern JavaScript technologies including JQuery, AJAX, JSON, and RESTful APIs.
In this course, you will again be an independent developer the Northside Youth Soccer League has hired to create an app to give their players and parents easy on-the-go access to the league's game schedules. To avoid the hassles of native apps, they would like this to be a mobile web app. You will design and develop the mobile web app, and will add features to the app that are specific to mobile devices, such as location-based features so parents can see where they are in relation to the soccer field.
In this course, you have been hired by a board game company looking to use their brand recognition to market online games with a retro touch. In particular, they want your team to create a multi-player online version of a Salvo-like game engine. Salvo was a pencil and paper game that was the basis for the popular Battleship game. The basic idea involves guessing where other players have hidden objects. This can be varied to create many different kinds of games with different user interfaces. Your job will be to create a front-end mobile-friendly web application that game players interact with, and a back-end game server to manage the games, scoring, and player profiles. You will use the Angular JavaScript library for the front-end client, and the Spring Boot framework for the Java-based RESTful web server.
As you work, you will have constant access to a unique automated mentor, employing natural-language processing technology derived from our decades of artificial intelligence research. The automated mentor can provide immediate answers to most task-related student questions posed to it in plain English, and it can provide immediate feedback on your work. Of course, human mentors will still be available in those rare instances in which you need help with a unique problem. Automated mentoring will speed your progress through the program and will significantly lower the program's tuition cost, making preparation for a software development career more widely accessible.
You will be assigned to a small team made up of fellow students, and you will meet regularly in an online environment to discuss your work. A human mentor can join your group meeting, as required, to assist in solving unique problems.
See our immersive, story-centered curricula in action. This demo is actual content from an early task in this course.
Note: due to the technical nature of this course, this course is built for and best viewed on a laptop/desktop (not mobile).
There are no prerequisites for this program.
The Software Development Program is divided into two parts:
Students can choose to attend:
- Full time (30 hours per week) for 24 weeks,
- Part time (15 hours per week) for 48 weeks.
The cost for this program is
$7,900.
The program comes with our Employment Guarantee and is subject to our Refund Policy.
Students will get an offer for a full-time job, a contracting job, or paid internship working at least 35 hours per week within six months of successfully completing a certificate program.
If a student voluntarily elects to accept a job working fewer than 35 hours per week and stops seeking full-time employment as a result, that student will forfeit the employment guarantee.
If a student meets the above criteria and does not receive a job offer within six months of completing the program they will be issued a refund for 100% of tuition they have paid.
At the conclusion of the first course of the Data Analytics program (three to four full-time weeks into the program), a committee of mentors will decide, based on the student's progress and quality of work, if the student is likely to succeed in a professional career. If the committee decides that he or she is not, the student can elect to leave the program with a 90% refund or to continue the program without an employment guarantee.
Successfully complete the entire program, submitting work judged to be satisfactory by our mentors for all projects in the program.
Be 21 years or older.
Live in a top 20 metropolitan area of the USA or be willing to locate to one.Be eligible and willing to work in the USA.
Be proficient in English.
Develop and actively maintain a portfolio in Github.
Develop an acceptable professional resume and accompanying LinkedIn profile.
Be available for a minimum of 3 job interviews per week.
Apply for jobs with at least 8 prospective employers each week.
Submit any analytics challenges required for job applications promptly.
Accept any legitimate job offer meeting the conditions above.
Are you driven to solve business and engineering problems? Do you see complexity as a challenge rather than a barrier? You may not have a technical background, be a programmer, or know much about statistics, but you are willing to work hard and to learn as you go. If this description fits you, the Data Analytics and Big Data Program may be for you.
This immersive online program will teach you how to make data-driven decisions. If you're a self-starter looking to dive in to a highly competitive workforce, this program will teach you the skills that will guarantee you a job
In this course you will be working under Blackwell's Chief Technology Officer Danielle Sherman, as a member of the Blackwell Electronics eCommerce Team. Blackwell Electronics has been a successful consumer electronics retailer in the southeastern United States for over 40 years. Last year, the company launched an eCommerce website. Your job is to use data mining and machine-learning techniques to investigate the patterns in customer sales data and provide insight into customer buying trends and preferences. The inferences you draw from the patterns in the data will help the business make data-driven decisions about sales and marketing activities.
First you will install the RapidMiner Data Science Platform and use it to understand the relationship between customer demographics and purchasing behavior. Next, you will use Regression and Classification machine learning algorithms in RapidMiner to assist you with proposing business decisions based on your analysis. Finally, you will present to management, explaining your insights and suggestions for data mining process improvements.
In this course, you will continue to work with Danielle Sherman, the Chief Technology Officer at Blackwell Electronics. Blackwell Electronics is a successful consumer electronics retailer with both bricks & mortar stores in the southeastern United States and an eCommerce site. They have recently begun to leverage the data collected from online and in-store transactions to gain insight into their customers' purchasing behavior. Your job is to extend their application of data mining methods to develop predictive models and you'll be using R to accomplish this. In this course, you will use machine learning methods to predict which brand of computer products Blackwell customers prefer based on customer demographics collected from a marketing survey, and then you will go on to determine associations between products that be used to drive sales-oriented initiatives such as recommender systems like the ones used by Amazon and other eCommerce sites. Finally, you will present to management, explaining your insights and suggestions for data mining process improvements.
Increasingly, technology companies are applying data analytics techniques to the masses of data generated by devices such as smart phones, appliances, vehicles, electric meters, et cetera. The ability to deal with data of these types will prove to be a high-demand skill for data analysts as applications of commercial interest increasingly go beyond business intelligence. The skills you will learn are applicable to a wide variety of data analytics projects and will enable you to start working on problems that benefit from the application of machine learning and statistical analysis techniques to sensor (and other) data.
In this course, you'll be working for an "Internet of Things" technology start-up that wants to use Data Analytics to solve two difficult problems in the physical world:
1. Smart energy usage: Modeling patterns of energy usage by time of day and day of the year in a typical residence whose electrical system is monitored by multiple sub-meters.
2. Indoor locationing: Determining a person's physical position in a multi-building indoor space using wifi fingerprinting.
You'll use R to create visualizations, and then you will generate descriptive statistics and predictive models using both statistical classifiers and linear regression techniques. Finally, you'll present the results to the start-up's management, explaining strengths and weaknesses of the approaches you implemented and making suggestions for further improvement.
In this course, module, you will be working as a data analyst for Alert Analytics, a data analytics consulting firm. On your first project for the firm, Alert's founding partner and SVP Michael Ortiz has asked you to take over for a recently-transferred analyst who has been working on a big data project for Helio, a smart phone and tablet app developer. Helio is working with a government health agency to create a suite of smart phone medical apps for use by aid workers in developing countries. The government agency will be providing workers with technical support services, but they need to limit the support to a single model of smart phone and operating system. To select the most appropriate device, Helio has engaged Alert Analytics to conduct a broad-based web sentiment analysis to gain insight into the attitudes toward the devices. Your job is to conduct this analysis.
First, you will set up and become familiar with the Amazon Web Services (AWS) computing environment. Next, you will use the AWS Elastic Map Reduce (EMR) platform to run a series of Hadoop Streaming jobs that will collect large amounts of smart phone-related web pages from a massive repository of web data called Common Crawl. Once this data has been gathered, you will then compile it into a data matrix where you can then use a machine learning to develop a predictive model that will label the data with the websites' sentiment toward the devices. Finally, you will prepare a presentation and summary of your findings from the analysis for an executive audience and report on lessons learned during the process.
In this course, you are a Data Scientist for Credit One, a third-party credit rating authority that provides retail customer credit approval services to businesses.
Credit One has tasked you with examining current customer demographics to better understand what traits might relate to whether or not a customer is likely to default on their current credit obligations. Understanding this is vital to the success of Credit One because their business model depends on customers paying their debts.
Your job as a Data Scientist will be to identify which customer attributes relate significantly to customer default rates and to build a predictive model that Customer One can use to better classify potential customers as being 'at-risk', compared to previously implemented models. You will use ensemble machine learning classification methods in Python for this task.
You will then go on to complete a capstone project of your own choice, again using Python.
Students work on authentic problems with an experienced mentor as their guide. Mentors don't lecture but rather help students learn and develop skills as relevant to the work they are doing. Mentors provide in-depth feedback on student projects and make recommendations for improvement spurring additional student growth in the process.
See our immersive, story-centered curricula in action. This demo is actual content from an early task in this course. Note: due to the technical nature of this course, this course is built for and best viewed on a laptop/desktop (not mobile).
At least a year of work experience
- Although the course can be taught to anyone, our experience suggests that individuals that have some work experience are more likely to succeed.
Familiarity with Windows, Mac, or Linux operating system, specifically:
- Creating and managing folders within folders
- Creating and extracting files from zip archives
- Elementary administrative tasks (e.g., installing software requiring admin privileges)
- Basic familiarity with Microsoft Office or an equivalent productivity suite
Basic knowledge of statistics may accelerate your initial progress in the program, but all necessary statistical concepts will be introduced during each course.
You work online, attend regularly scheduled meetings and make appointments with your mentor just as you would do with a real-world supervisor.
Students can choose to attend:
- Full time (30 hours per week) for 20 weeks, or
- Part time (15 hours per week) for 40 weeks.
The cost for this program is
$7,900.
The program comes with our Employment Guarantee and is subject to our Refund Policy.
Students will get an offer for a full-time job, a contracting job, or paid internship working at least 35 hours per week within six months of successfully completing a certificate program.
If a student voluntarily elects to accept a job working fewer than 35 hours per week and stops seeking full-time employment as a result, that student will forfeit the employment guarantee.
If a student meets the above criteria and does not receive a job offer within six months of completing the program they will be issued a refund for 100% of tuition they have paid.
At the conclusion of the first course of the Data Analytics program (three to four full-time weeks into the program), a committee of mentors will decide, based on the student's progress and quality of work, if the student is likely to succeed in a professional career. If the committee decides that he or she is not, the student can elect to leave the program with a 90% refund or to continue the program without an employment guarantee.
Successfully complete the entire program, submitting work judged to be satisfactory by our mentors for all projects in the program.
Be 21 years or older.
Live in a top 20 metropolitan area of the USA or be willing to locate to one.Be eligible and willing to work in the USA.
Be proficient in English.
Develop and actively maintain a portfolio in Github.
Develop an acceptable professional resume and accompanying LinkedIn profile.
Be available for a minimum of 3 job interviews per week.
Apply for jobs with at least 8 prospective employers each week.
Submit any analytics challenges required for job applications promptly.
Accept any legitimate job offer meeting the conditions above.
Do you become completely caught up in finding solutions to difficult problems and puzzles? You don't expect someone to tell you the answer and take pride in figuring things out for yourself. Your search might start with Google, but it doesn't end there. Once you've become immersed in solving a problem, you can't let it go until you've succeeded at finding the best solution. If this description fits you, the Cyber Attack Academy may be for you.
This immersive online program will teach you how to ensure the security of critical information infrastructure. If you're a self-starter looking to dive into one of the fastest-growing industries today, this program will teach you the skills that will guarantee you a job.
Students work on authentic problems with an experienced mentor as their guide. Mentors don't lecture but rather help students learn and develop skills as relevant to the work they are doing. Mentors provide in-depth feedback on student projects and make recommendations for improvement spurring additional student growth in the process.
See our immersive, story-centered curricula in action. This demo is actual content from an early task in this course.
Note: due to the technical nature of this course, this course is built for and best viewed on a laptop/desktop (not mobile).
There are no prerequisites for this program.
You work online, attend regularly scheduled meetings and make appointments with your mentor just as you would do with a real-world supervisor.
The program requires a 26 week commitment at a minimum of 30 hours a week. We are currently admitting students on a rolling basis.
The cost for this program is
$7,900.
The program comes with our Employment Guarantee and is subject to our Refund Policy.
Students will get an offer for a full-time job, a contracting job, or paid internship working at least 35 hours per week within six months of successfully completing a certificate program.
If a student voluntarily elects to accept a job working fewer than 35 hours per week and stops seeking full-time employment as a result, that student will forfeit the employment guarantee.
If a student meets the above criteria and does not receive a job offer within six months of completing the program they will be issued a refund for 100% of tuition they have paid.
At the conclusion of the first course of the Data Analytics program (three to four full-time weeks into the program), a committee of mentors will decide, based on the student's progress and quality of work, if the student is likely to succeed in a professional career. If the committee decides that he or she is not, the student can elect to leave the program with a 90% refund or to continue the program without an employment guarantee.
Successfully complete the entire program, submitting work judged to be satisfactory by our mentors for all projects in the program.
Be 21 years or older.
Live in a top 20 metropolitan area of the USA or be willing to locate to one.Be eligible and willing to work in the USA.
Be proficient in English.
Develop and actively maintain a portfolio in Github.
Develop an acceptable professional resume and accompanying LinkedIn profile.
Be available for a minimum of 3 job interviews per week.
Apply for jobs with at least 8 prospective employers each week.
Submit any analytics challenges required for job applications promptly.
Accept any legitimate job offer meeting the conditions above.