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Berkeley Global
Ryan Nichols
is the founder and owner Inbound Web Services.
Current Student, Program in Data Science
Read Ryan Nichols' Story.
Build on your current work experience in data analysis or level-up your data science know-how with our fully online Program in Data Science! Through practical, hands-on online courses, you learn from working professionals on how to perform advanced data wrangling, data mining, statistical modeling and usage of machine learning techniques to derive meaning and understanding of large and complex data sets.
Get ready to fill a variety of data scientist roles in tech, health care, defense, finance, business and many others.
2,000–3,000
—Job openings per month
EMSI/Lightcast
After collecting, storing, retrieving and analyzing data, learn to build and evaluate data models in order to produce industry-standard data visualizations that succinctly and effectively communicate the results and your recommendations.
Through our online curriculum, you will take an in-depth focus into Python and cloud computing, have numerous opportunities to practice more advanced statistics, integrate machine learning algorithms, and perform advanced work with databases and big data.
The field of data science has matured to include a suite of toolkits and methods, which our courses prepare you to master.
By completing this program, you will be able to:
- Apply statistics and probability essentials to manipulate and preprocess data for feature transformation, dimensionality reduction and model evaluation.
- Utilize essentials of linear algebra and multivariate calculus in machine learning to preprocess, transform and evaluate a variety of features and predictors for data models.
- Employ machine learning algorithms and objective functions to optimize experiments and predictive modeling, such as cost/objective, likelihood, error and gradient descent.
- Master essential programming skills for statistical modeling and data analysis using Python, R or both.
- Demonstrate familiarity with essential data analytics methodologies and procedures such as data wrangling and preprocessing.
- Become fluent in Excel, Tableau, Hadoop, SQL, GraphQL and Spark.
- Create data visualizations that utilize data, geometric, mapping, scale, labels and ethical-centricity.
- Perform experiments for continuous variable prediction and discrete variable prediction, and make predictions using machine learning algorithms.