Career Services with The Data Incubator

In addition to the in-demand skills and programs you'll learn in our Data Analytics Program, we'll also help you craft your resume and hone your interview skills so you can shine in front of potential employers.

Our career services team will work with you and our pool of hiring partners to find you amazing opportunities you won't see anywhere else. You could be working an exciting new career in a matter of months for a leading company like:

About the Data Analytics Program

Prerequisites:

• Elementary programming knowledge
• Familiarity with statistics

Upon completion of this program, you'll be able to:

• Land an exciting job in the ever-growing field of data
• Extract, clean, and analyze data using Python
• Create clear and strong visualizations with Tableau
• Make better decisions by building predictive models with Python
• Help your company solve business problems using data-driven insights

Program Outline

Data Wrangling with Python

Between 60-73% of an organization's data is untouched for analysis, leaving valuable opportunities on the table. In this section, you'll learn the Python tools and programs needed to start processing that unused data, distilling key insights and trends, and begin turning that information into easily digestible, business-focused findings. Topics include:

• Python data structures
• Python control structures
• Common file and data formats
• Object-oriented programming (OOP) in Python
• NumPy and arrays
• Ingesting, filtering, and merging data with Pandas
• Aggregating data with Pandas
• Handling time series data with Pandas
• Visualizing data with Pandas and matplotlib
• String processing with regular expressions

SQL

Companies collect data from a number of different places, but they don't all arrive in the same way. In this section, you'll learn how to use Structured Query Language (SQL) to extract and analyze data stored in multiple databases, integrate SQL queries with Python, and begin to process the mountain of untouched data your organization has sitting around. Topics include:

• Basic queries and filtering data
• Joining tables
• Aggregation functions
• Creating tables and ingesting data
• Use of temp tables and views
• Interacting with SQL from Python
• Uses of SQL outside of RDS

Data Communication

Many business professionals lack the data literacy skills to interpret and understand the insights drawn by data analysts, and aren't comfortable accessing or using the data at their disposal. In this section, you'll use Python and Tableau to create powerful and easy-to-follow visualizations of the data you collect, understand how to best present your findings to different audiences, and find the right problems to solve for your organization. Topics include:

• Components of visualization
• The power of different visual cues
• Exploratory and explanatory visualizations
• Visualization tools using Python
• Loading data into Tableau
• Visualizations with Tableau
• Choosing the right problems to solve
• Metrics and levels
• Communicating results

Machine Learning

Every business leader wishes they could predict the future of their market and their business. With machine learning, you can do just that. In this section, you'll learn the basics of machine learning so that you can start predicting trends that your organization can use to streamline the business. Topics include:

• Machine learning basics
• Scikit-learn for machine learning
• Techniques and metrics of regression
• Linear regression
• Overfitting and cross-validation
• Techniques and metrics of classification
• Logistic regression
• Dimensionality reduction with PCA
• Clustering
• Feature engineering with transformers

Ready to jumpstart your data career?

Apply now and begin your journey toward becoming a leading data analyst.