Diploma in Data Science

• Get an introduction to the fundamentals of Python for Data Science including programming, how to organize your data with data structures, and basic algorithms. (Module 1)
• Review concepts such as linear algebra, gradients, optimization, confidence intervals & testing, distributions, and linear models. Math and statistics are a fundamental skill for anyone working with large amounts of data. (Module 2)
• Explore supervised learning, clustering, and embedding while getting a solid overview of machine learning, an application of artificial intelligence that provides systems with the ability to automatically learn and improve from experience without being explicitly programmed. (Module 3)
• Learn to leverage different data formats, from raw data to production analytical or predictive uses and acquire knowledge in relational databases (SQL), MapReduce framework for NoSQL schemas, network/graphical data, text data (NLP), sequential data (time series), and image data. (Module 4)
• Gain the necessary skills to manage a real project including effective data analysis and presentation, object oriented & other programming paradigms, source code and data management, as well as deployment and maintenance. Being a good Data Scientist requires the ability to clearly communicate information to stakeholders. (Module 5)
• Work on a real-world project based on data including presenting an analysis of the data, justifying the approach, presenting a solution and demonstrating statistically the efficacy of your solution. (Module 6)
• Finish the program with a capstone solo project, during which you will develop a machine learning solution on complex real-world data, and deploy a prototype microservice. You will be responsible for all decisions from what data to use and how, to the data pipeline and model. (Module 7)

No need to commute over to campus for this program. Connect online with your instructor and classmates in our virtual classroom powered by Zoom and Slack. Ask questions in real-time and take part in group discussions, just as you would in a physical classroom. Outside of lectures, you'll often find yourself wanting a little bit of extra guidance for your class-work. Using our queue system, you'll be able to lineup for 1-1 support from Technical Coaches as needed. Finally, learning online doesn’t mean learning in isolation. Slack is active pretty much at all hours of the day. We also host a wide array of online networking events, Q&A sessions with alumni, and encourage the use of virtual study sessions amongst classmates.

• Anyone who wants to start a career as a data scientist or data analyst;
• Anyone who wants to upgrade their current skill set and employability, specifically those working in tech (such as marketers, designers, project managers, etc.);
• Students who want to improve their skill set by data science.

For complete course details and information on how to register, visit concordiabootcamps.ca.