Great news: We’re launching four new and improved Data Scientist career paths and one BI Data Analyst career path.
Data science is all about using data to identify pathways to improvement — and our data science content is no exception. We took a hard look at our Data Science career path and identified several ways we could make the new Data Scientist career path a better experience for you.
We’re restructuring the paths to allow you to specialize in the kind of data science that you want to do while building a foundation in general data science. The paths are now 10-40% shorter and more focused on four different types of Data Science. Our goal is to help you reach your goals faster while still equipping you with all the skills you need to be a successful Data Scientist.
That’s why we’re launching five new career paths:
- Machine Learning/ Algorithms Data Scientist
- Analytics Data Scientist
- Inference Data Scientist
- Natural Language Processing Data Scientist
- BI Data Analyst
All of the Data Scientist career paths begin with the same core content (which is also our Foundations of Data Science skill path). After building that foundation, you can keep or change your specialization to fit your goals — and transfer your progress automatically.
We’ve trimmed each career path to focus on only what you need to know for the type of job you are targeting. At the same time, we’ve created content on Data Literacy and Exploratory Data Analysis that will apply to all Data Scientists. We’ve also created courses on topics that fill out specialist roles, such as Handling Missing Data, Causal Inference, Feature Engineering, Tableau, and Excel.
The Python unit has all new projects focused on real-world data science problems, and we’ve added targeted portfolio projects to show off your skills. Additionally, we’ve rearranged some of the content so that it better reflects the data science workflow. Finally, we’ve integrated connective tissue to clarify what you’re covering in each unit and how it relates to your overall Data Scientist career path journey.
How does this impact you?
If you’ve already started or completed the Data Science path, you will be enrolled in the Data Scientist – Machine Learning/Algorithms and will see some new content added and some other content removed. If you’ve already started or completed the Data Analyst career path, you will be enrolled in the Data Scientist – Analytics career path.
Anything you’ve already completed will remain completed, and progress on those items will transfer; however, you may notice that your overall progress decreased (or increased), depending on where you were in the path.
The path will be updated on May 16th, 2022.
Take a look below to get an overview of the updates.
Updates in the Data Scientist Career Paths
New content covering:
- Introduction to Data & Data Literacy
- Thinking about Data
- Visualizing Data
- Analyzing Data
- Working with Jupyter Notebooks
- Data Acquisition
- Summarizing a Single Feature
- Summarizing the Relationship between Two Features
- Updates to Probability and Statistics
- Handling Missing Data
- BI Dashboards with Tableau (Analytics, Inference, and BI Data Analyst only)
- Spreadsheets with Excel (Analytics, Inference, and BI Data Analyst only)
- Advanced SQL (Analytics only)
- Introduction to Feature Engineering (Machine Learning only)
- Transforming Data into Features (Machine Learning only)
- Feature Selection Methods (Machine Learning only)
- Feature Engineering by Reducing Dimensionality (Machine Learning only)
- Calculus & Linear Algebra (Machine Learning Only)
- Conceptual Foundations of Causal Inference (Inference only)
- Matching & Weighting Methods (Inference only)
- Regression Discontinuity Design & Instrumental Variables (Inference only)
- Difference in Differences (Inference only)
Updates to Open-ended Portfolio Projects:
- Data Visualization
- Exploratory Data Analysis
- Data Analysis
- Machine Learning
- Final Portfolio Project
We’re updating our Data Scientist career paths so that it’s an even better learning experience. You can now focus on the exact skills you need to earn a job while developing a foundation in the core tools for working with data. Dive into the data now!