ICT Ignite Plus - Data Science
General
- Workforce Development
- 65 learners; teams of 4
- 80 hours per learner
- Dates set by projects
- Learners apply to projects
- A maximum of 4 team(s) or 4 learner(s) per project.
Preferred companies
- 28/30 project matches
- Canada
- Payment by funder C$2,000.00
- Any company type
- Any industries
Categories
Skills
Overview
- What is the main goal for this project?
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80-hour, fully-subsidized, Data Science or Data Analytics internships for Canadian employers.
Learners are graduates of Lighthouse Labs Data Science Program. They have recently completed intensive, immersive training emerging with a robust skill set encompassing data manipulation, machine learning, and predictive modeling. They are proficient in programming languages such as Python and SQL, allowing them to extract insights from complex datasets and build data-driven solutions for your project.
Learners are paid a $2000 CAD stipend on completion of the project by Riipen. Employers are not required to provide payment
We are excited to share that we have a wage subsidy program available if you wish to hire a ICT Ignite Plus learner after their project is complete. The program spots are limited and on a first-come-first serve basis. Details can be found here.
Submit a project here for our ICT Ignite team to review. Once approved, learners are not guaranteed yet, but they will apply to your project directly. You will have a chance to review, assess and accept applications, and 2-4 learners should be accepted per project. Get specific in your project description about the skills you're looking for in order to attract the most suitable applicants.
If you have questions or need help drafting your project content please email us at ictignite@riipen.com. You can also find all of our help articles here.
ICT Ignite Plus is offered as part of the ICT Boost Initiative. Funded in part by the Government of Canada's Sectoral Workforce Solutions Program (SWSP).
- Learner skills
- Setting up a data science environment using anaconda, vscode, git, and virtual environments, Python, postgresql, git, and jupyter notebook, Data wrangling, data manipulation, pandas, apis, and the etl process, Data visualization with tools like tableau, matplotlib, seaborn, plotly, Probability theory, statistics, and linear algebra using numpy and statsmodels, Relational and non-relational databases, Development process using tools like pickle, joblib, and flask, Elements of machine learning like supervised learning, unsupervised learning, deep learning (stretch content), nlp (natural language processing), time series, and recommender systems using sci-kit learn, tensorflow and keras.
- What tasks will learners need to complete to achieve the project goal?
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Graduates of our comprehensive Data Science curriculum emerge with a versatile skill set that empowers their success in the data-driven landscape. They demonstrate proficiency in data manipulation, analysis, and visualization through tools like Python and SQL. Skillfully extracting insights from intricate datasets, they boast hands-on expertise in data cleaning, transforming, modeling, and employing data visualization libraries. Moreover, they possess a robust grasp of statistical concepts, facilitating data-driven decisions by presenting their insightful conclusions to stakeholders. Rooted in problem-solving and critical thinking, they are prepared to offer valuable insights to your project.
Deliverables will vary depending on the project scope. At the conclusion of the project you will have assets that can be used to further your business goals, such as a completed cyber security analysis report.
Note: If learners are completing confidential work that you do not want shared through Riipen, you can create and sign off on a timesheet for the learner. In this case, we might also recommend that you have the learners sign an NDA before starting your project. You can use the Agreements feature to do this.
Project Examples
- Projects should be approximately 80 hours in length per learner and are to be completed over 2-8 weeks.
- Each project should require the contributions of 2-4 learners (160-320 hours in total).
- Check out this guide on best practices for working with ICT Ignite learners.
- Given the short, remote nature of ICT Ignite Plus we require a project-based experience. If your project looks like a job posting, we can not accept it. Please provide a concrete scope for the learner’s work and limit their work to a specific project.
- We have pinned an example project template to this experience which you can use as a starting point.
- If you choose to use a template from our library, ensure that you have added as much context for your business needs as possible. Our team will not accept any projects that were created from a template without sufficient customization. While learners will interact with you to complete the project, we want them to be able to understand the scope of the project by reading your project details. This will also help to ensure that you have the right learners applying to your projects!
Additional company criteria
Companies must answer the following questions to submit a match request to this experience:
I confirm that I have read and understand the Terms and Conditions of this program.
I confirm I will work with 2-4 learners for this project.
I will review and respond to learner applications within 5 business days.
I understand that learners can only complete one project and may be applying to multiple projects. Learners are responsible for choosing the one project they wish to start & work on.
I understand that I must provide ongoing mentorship and guidance to the learner(s) that are working on my project(s). I must be responsive to any questions, and check in on progress to help ensure a good result.
I will evaluate the learners' final project submissions within 5 business days, offering feedback that can be utilized by the learners to strengthen their resumes and LinkedIn profiles.
How do you plan to onboard the learners to your tools and technology stack?
What format is the data in currently?
How large is the data set?
How will you share the data?