Data Science Classes Los Angeles, CA

Learn to problem solve, and effectively communicate, like an analyst. This course teaches you to use industry-standard tools to make ethical, data-driven decisions. Experience hands-on training to master SQL, Excel, Tableau, PowerBI, and Python – tools listed in virtually every data analytics job posting across industries.

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.

Create robust predictive models with statistics and Python programming. Build confidence and credibility to tackle complex machine learning problems on the job. This course is offered in person and live online, in a remote classroom setting.

In this course, students expand their Python programming skills into machine learning and algorithms that can independently learn patterns and make decisions. The course begins with linear and logistic regressions, the most time-tested and reliable tools for approaching a machine learning problem. Students then progress to algorithms with a different theoretical basis, such as k-nearest neighbors, decision trees, and random forest. This will bring important statistical concepts to the forefront, such as bias, variance, and overfitting. Participants also learn how to measure the accuracy of your models, as well as tips for choosing effective features and algorithms.

In this data science bootcamp, students will build programming skills and data analysis skills using Python. This course is open to beginners and is meant to get individuals up and running with Python programming and data science to generate insights from data. Topics covered include programming fundamentals, working with data frames, data analysis, data visualization, and statistical analysis. This course offers flexible scheduling options and a free retake for students to refresh the materials.

This course on data wrangling with Python offers a 3-day comprehensive introduction. The purpose of this course is to give an immersive foundation that equips students with the most critical data analysis tools. Students will learn how to work with NumPy, Pandas, and MatPlotLib to calculate descriptive statistics, work with alternative data sources, and scrape web pages. The course culminates with a real-life data wrangling project.

This 2-day course provides a deep-dive into using Python for data analysis. Students will get comfortable with the basics of Python programming and start working with Numpy Arrays, pandas, and MATPLOTLIB to perform data analysis and create data visualizations. This intensive course is meant to quickly get beginners in Python up to speed on performing data analysis and visualization in Python.

In this Python automation course, students will learn to automate tasks using Python for various applications. This course is meant for those with prior Python experience looking to learn automation techniques like scheduling programs, updating spreadsheets, and web scraping. Topics include HTML and CSS basics, web scraping techniques, working with spreadsheets using Python, and scheduling scripts. This course offers flexible scheduling options plus a free retake for students to refresh the material.

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.

If you have problems spelling Data Science Fundamentals, this 5-week introductory course is for you. This course is ideal for people like old-school business analysis, complete beginners, and non-technology managers. Using cornerstones like Excel, SPSS, and Python, students learn basic statistical methods which help them solve simple statistical problems. This hands-on course incorporates a variety of techniques, such as lab exercises, pencil-and-paper note taking, and laptop usage, to help students truly connect with the course content and acquire the tools they need to improve their professional careers.

Explore the evolving data science domain in this 10-week intermediate level course. Data science effectively answers a number of questions, and students learn how to tap into this knowledge. Students acquire real-world skills such as data science notebook server configuration, the R programming language, problem statement preparation, and the basics of machine learning. Students who have basic Python skills usually excel in this class.

Find evidence-based solutions to real-world problems with a four-class Data Science Certificate program. Students may choose from an intensive 10-week option or spread their learning out for up to twenty-four months. Students immerse themselves in concepts like machine learning, data management and visualization, and statistical models, which prepares them for successful careers. Furthermore, students get hands-on experience with industry tools like Python, NoSQL, and Hadoop. To master this area, which is partly science and partly art, students take Introduction to Data Science, Exploratory Visualization and Data ANalysis, Managing Big Data with Hadoop, and Machine Learning. Students with some data science experience or who have taken a basic data science course usually excel in this certificate program.

Analyze data and use it to solve real-world problems with this 10-week Python course. This platform enables users to leverage complex data into an easy-to-understand format. Primarily using Pandas, a key data analysis platform, students learn to prepare, cleanse, format, convert, and present data. Use of statistical models and some basic data visualization techniques greatly assists this process. Course prerequisites include a beginner Python programming course or equivalent experience.

Python Advanced course is a 12-hour course that will teach you how to connect to databases and complete data analytics in Python. You'll learn how to visualize data using Matplotlib and import different types of data using Pandas.

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

This Python and machine learning course is a 2-day bootcamp designed for individuals with some familiarity with Python programming looking to advance their skill set. In this hands-on bootcamp, students will learn how to use some Python data science libraries and various machine learning techniques. Day one of the bootcamp focuses on introducing students to two data science libraries (NumPy and Pandas), best practices for preparing data, an intro to machine learning, and regression analysis. Day two starts off with cross validation and regularization of data, concludes with classification, and brings everything learned in days one and two together.

This SQL bootcamp is a beginner-friendly workshop designed for individuals with no prior knowledge of SQL who are eager to learn. In this hands-on workshop, students will learn the basics of SQL syntax and how databases are organized. Students in this course will also learn how to query data, aggregate data with statistical functions (SUM, AVG, COUNT, etc.), group data, and use conditional operators (=, <, >, etc.) to sort and filter data, and much more. Students will also learn when and how to use UNIONs and JOINs to merge data to spot trends and other insights.

This 2-day course on Python with data science is intended for software developers, IT architects, and data scientists. This course will build on their knowledge of statistics and programming, teaching them the theoretical and technical aspects of the use for Python. Students will learn about the history and purpose of data science, life-cycle phases of data analytics, methods for repairing and normalizing data, and how to aggregate and group data. Students will also complete 10 lab exercises.

This comprehensive 4-week computer science program was designed with experienced web developers in mind to help achieve a deeper understanding for data structures, algorithmic thinking, and modern blockchain applications. The course covers a broad range of advanced computer science concepts and tools, including JavaScript syntax, Arrow Functions, Hash tables, algorithms, whiteboarding, building a Node app, working with APIs, Web sockets, Task automation, MongoDB, ORMs, a database review, and more. The course concludes with a final project, where students will have an opportunity to showcase the knowledge they gained in the program by building a complex full-stack application.