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Microcredential in Data Analytics with Python
Want to jump-start or advance your career in Data Analytics but don’t have a background in programming?
Composed of only two courses, it covers the essentials of data analytics and data science using Python, one of the most in-demand programming languages in the field today. The microcredential aims to give you the practical skills needed to structure, read, and analyze various types of data and create powerful visualizations to communicate insights with impact.
You can complete this microcredential within one semester and gain hands-on experience and skills that will set you apart in the field. Upon successful completion of the Microcredential, you will receive a Digital Badge and an Attestation of Completion.
Type: Microcredential Courses: 2 Schedule: Part-time Delivery: Virtual Time to complete: 1 semester Questions? pd.conted [at] mcgill.ca
Python: The most in-demand skill in Data Analytics job postings
Data Analytics Job Postings Canada, January 2022 – Dec 2022
Source: Lightcast™ . 2022
Introductory Data Science for Business Decisions
30 hours over 4 weeks
Introduction to fundamental principles of data science, data collection, exploration, and visualization techniques. Focus is placed on how data science supports business decision-making, translating data insights into business value, new business models and products, opportunities and challenges faced by data-driven businesses.
Introduction to Data Analytics with Python
30 hours over 4 weeks
Types of data analytics. Connecting business problems to analytics techniques and methods. The analytics process: identification, extraction, cleaning, transformation, analysis, and interpretation. Producing and improving data science and machine learning models and assessing their performance. Data analysis and modelling using Python.
Upon completion of these courses, participants should be able to:
- Apply basic Python skills and techniques to solve different data science challenges
- Carry out data analysis activities using key Python data science packages
- Connect to data, clean and prepare data for data science work using Python
- Visualize the results of data exploration and analysis using different Python libraries
- Understand and apply basic statistical techniques to solve data science problems
- Select the appropriate machine learning algorithm for a specific problem
- Produce machine learning models using Python libraries
- Evaluate and improve prediction model performance using different techniques
- Reflect on key ethical and privacy issues raised by using data science tools and techniques
Proof of English proficiency is not required to enrol in this microcredential. However, a good command of English is necessary to perform well and complete the courses.
Please select individual course links for pricing and dates. Register for both courses as part of this Microcredential and save $200.