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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 course covers the skills needed to become a Data Analyst or Business Analyst, including data analytics fundamentals, visualization with Tableau, using Python to clean and manipulate data, and how to work with relational databases. One-on-one mentoring is included.

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.

In this program, participants will learn the key skills and tools needed to succeed as a data analyst, including Excel, SQL, and Tableau. Attendees will learn how to use Excel to create graphs, summarize data with PivotTables, and analyze data. In SQL, attendees will learn the essentials of relational databases, queries, functions, and more. Finally, participants will learn Tableau to create visualizations to express their data. The program is open to beginners and has flexible scheduling options. Tuition includes hands-on training, a free retake, and training manuals for each course.

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.

Data Analytics Flex is a 6-month part-time program designed to get you a job as a data analyst. You will begin by learning how to master Excel and storytell with Powerpoint. Afterwards, you'll learn how to query data using SQL and visualize data using Tableau. Once you've mastered these building blocks, you'll receive business case studies to simulate real-world work projects and you'll also be exposed to statistics. Finally, you'll learn how to clean data using Python and work on your capstone project. This program comes with a tuition backed guarantee if you don't land a job within 6 months of graduation.

In this 8-day intensive Data Analytics bootcamp, students with little to no background in data analytics will learn how to use Microsoft Excel, SQL, and Tableau to summarize, display, and discover key insights hidden in data sets. By the end of this bootcamp, students will be able to use Excel to aggregate and summarize data, sort data with PivotTables, create charts and tables in Excel, use SQL to filter and sort large data sets, use advanced database queries, create visualizations with Tableau, and much more. Students will also be able to reinforce what they learn through the numerous projects they encounter throughout the course. This course also offers a free retake within six months to allow students to revisit any concepts needing to be refreshed and walk away with a much stronger grasp of the material.

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.

This data science bootcamp offers the ability to learn online with a 16-week full-time schedule or a 24-week part-time schedule. Students will learn how to use tools such as Python, R, Hadoop, and AWS to facilitate data visualization and analysis, machine and deep learning, and building statistical models. This program culminates in a professional capstone experience.

This 35-hour program offers a comprehensive introduction to R. This course teaches the skills needed to process, manipulate, and analyze data, create visualizations, and generate reports. The program begins with an overview of programming with R. It then moves on to the treatment of basic data elements, the use of “dplyr” to manipulate data, and how to create basic and advanced visualizations such as violin and mosaic plots, and time-series diagrams.

This six-week course teaches students how to use key components of Apache Hadoop, Spark, MapReduce, and more. Using platforms such as Databricks, Amazon Web Services, and Docker, students will learn how to use Python and cloud computing to run exercises. Students will complete five units on topics such as Hadoop, MapReduce, Apache Hive, Apache Pig, Apache Spark, and Amazon Web Services.

Data Science Immersive is a 5-month full-time program that will prepare you to be a data scientist. You don't have to pay anything until you receive a job that is more than $40,000. 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.

Data Analytics Immersion is a 4-month full-time program designed to get you a job as a data analyst. You won't have to pay until you get a job making at least $40,000. You will begin by learning how to master Excel and storytell with Powerpoint. Afterwards, you'll learn how to query data using SQL and visualize data using Tableau. Once you've mastered these building blocks, you'll receive business case studies to simulate real-world work projects and you'll also be exposed to statistics. Finally, you'll learn how to clean data using Python and work on your capstone project.

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.

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.

The Remote Data Analytics Bootcamp is a 9-week full-time program that will start by teaching you the basics of MySQL, Python, and Git. Once you've mastered the basics, it will introduce web scraping, API, and data cleaning concepts. Afterwards, you will learn about inferential statistics, probability, topics in business intelligence. Finally, the course will teach you how to build, train, and evaluate supervised and unsupervised machine learning models. You will complete three projects after each module and showcase your last project to your peers in a "Hackshow".

The Remote Data Analytics Part-Time Bootcamp is 24 weeks long that will start by teaching you the basics of MySQL, Python, and Git. Once you've mastered the basics, it will introduce web scraping, API, and data cleaning concepts. Afterwards, you will learn about inferential statistics, probability, topics in business intelligence. Finally, the course will teach you how to build, train, and evaluate supervised and unsupervised machine learning models. You will complete three projects after each module and showcase your last project to your peers in a "Hackshow".

Online Data Science Certificate is a 16-week comprehensive that will teach you teach you the entire data science workflow from start to finish. The program will start with data cleaning, visualization, and exploration concepts. Afterwards, it will teach you how to use various predictive algorithms and how to evaluate their performance. It also introduces boosting, ensemble, ranking, and linear regression methods that are important tools for data scientists. Finally, you will have an opportunity to use your knowledge and deploy your models using a dataset from Kaggle competitions.

This 10 week online course provides a broad overview on how data science should be incorporated in your business why it matters. It starts by explaining why the quality of your data matters then teaches you about how analysts extract insights from data. It discusses how managers should select which metrics to focus on to measure success depending on the type of data you have on hand. Once the basics are covered, it teaches you about machine learning, big data, and data ethics that managers and business leaders should know about.

Beginners welcome in this introduction to data analytics course, learning subjects such as organizing and analyzing data with Google Sheets as well as making charts and visualizations. Students also learn how to write database queries with SQL, explore Tableau, and gain an introduction to Python for data analysis.