Data Science Classes San Francisco, CA

This full-time, accredited data science bootcamp covers data wrangling and exploratory data analysis using Python's statistical and data visualization packages. It also teaches regression techniques, web scraping, classification techniques using supervised and unsupervised models, and natural language processing. Finally, the courses finishes off with a capstone data science project where students can showcase their knowledge and talent.

The Data Science Bootcamp from Flatiron is designed to be a comprehensive data science program for students to start careers in data science. The program runs for 15-weeks and covers the key components for data science, including SQL, Python, statistics, and machine learning. Students will start coding in Python using Jupyter notebooks, learn the statistics behind machine learning, apply machine learning techniques, and work on data science projects in this data science course. In addition to the coursework, students will receive career coaching and job support during the program.

This data science program is designed to help individuals with a math background and some familiarity with Python programming bolster their skills and get up to speed and launch their data career. Through their blended learning model, students will be able to hone their data skills through fundamental preparatory work, in-class project work, and though the support of a devoted career coach. Students in this course will start their data science journeys by learning fundamental concepts around Python programming and leveraging programming tools like GitHub. As the course progresses, students will explore additional programming concepts like NumPy, utilizing Unix commands, using Pandas to clean and extract data, and web scraping tools. The course also covers statistical modeling and regressions, machine learning models, NLP, and a few other advanced topics and trends that are helpful to data scientists of all levels.

In this comprehensive data science program, individuals will learn a variety of critical skills to become a data scientist. Students will learn to code with Python, create machine learning models, automate tasks like web scraping, and interact with databases using SQL. Topics include data analysis with Python's Numpy and Pandas packages, data visualization, predictive analytics, machine learning, SQL querying, Python automation, and web scraping. Students will learn hands-on by working in Python and SQL and will complete the program with the skills they need to enter the field of data science. This program offers flexible scheduling and provides a free retake for students to refresh the material.

This data science course is a 10-week, part-time program for individuals with backgrounds in programming or a quantitative field. Utilizing a hands-on approach, students learn by doing to build vibrant skills that are essential in any field that leverages big data. The course curriculum centers around Python programming and data exploration, data modeling, and machine learning. Graduates of the Data Science course will be able to showcase their strong understanding of Python programming and applied statistics through their capstone projects, which are also a great springboard to a career in data science.

This online data science program is meant to get students ready for a career in data science. The program covers the key components for data science, including SQL, Python, statistics, and machine learning. Students will start coding in Python using Jupyter notebooks, learn the statistics behind machine learning, apply machine learning techniques, and work on data science projects in this data science course. Students will also receive career coaching and job support during the program for help finding a job in data science. The online program offers flexible scheduling options, including full-time over 5 months, part-time over 10 months, and self-paced for up to 15 months.

Data Science Flex is a 6-month part-time program that will prepare you to to be a data scientist. This program comes with a tuition back guarantee if you can't land a job within 6 months after your graduation. To be accepted into this program, you will have to complete 3 weeks of prepwork and pass an assessment test before you start. Once you're accepted, you'll learn how to clean data using Python, query data using SQL, learn how to train and evaluate supervised and unsupervised machine learning models, and choose a track to specialize. You can deepdive in natural language processing, big data and spark, and deep learning with TensorFlow and Keras.

This data science program is a beginner-friendly bootcamp designed for individuals interested in learning the best practice of working with data and understanding how to gain insights from large data sets. In this hands-on bootcamp, students will get an overview of data science, including the various roles within data science and how to recognize and solve problems with data science. Students will also discuss how to use some well-known statistical models and how models fit into a data science project. Finally, students will explore various tools, including data visualization, analytical, and modeling tools essential in the field of data science.

Data Science Immersive Bootcamp is a 13-week full-time program that has four modules. To get accepted into the program, you'll have to pass a coding a challenge and a technical interview. However, they will provide study materials to help you succeed. Once you are accepted, you will learn Python and statistics in the first module. In the second, you will learn about machine learning and prediction. The third module will teach natural language processing and the fourth will be dedicated to your capstone project.

As of July 14, 2020, the Data Science Immersive course is not available.

This data analytics course is a 40-hour in-person or online program for individuals with no prior experience with data analytics. Utilizing a hands-on approach, students learn by doing in order to build vital and dynamic skills that are applicable in a wide range of industries. The course curriculum centers around the core processes all data analysts must know, including data collection, cleaning, analyzing, and data visualization best practices. Students also come away with hands-on experience using some of the most common tools in the industry, including Microsoft Excel, SQL, and Tableau. By the end of the course, students will have a better understanding of how to gain insights from data and feel more prepared for a possible career in data analytics.