Find & compare hands-on Data Science courses available live online (virtual/remote training). We’ve chosen over 100 of the best Data Science courses from the top training providers to help you find the perfect fit.
Learn Data Science as part of a comprehensive program or bootcamp. These programs teach a variety of skills including Data Science and are typically geared towards preparing you for a new career.
Students train in Digital Product Design for Web 3.0. Topics covered include the foundations of User Experience (UX) and User Interface (UI) design, design sprints, conducting research, prototyping, and digital product testing.
This course provides comprehensive foundational training in becoming a Product Manager. Students develop skills in market analysis, product ownership, product management methodologies, and product marketing.
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Here are some of the top Live Online schools offering Data Science training, including Noble Desktop (15 courses), General Assembly (9 courses), and Practical Programming (7 courses).
Founded in 1990, Noble Desktop offers part-time and full-immersion courses on anything you can think of from design and coding to business. Located in New York City and providing courses both online and in-person, Noble Desktop prides itself on accommodating dynamic courses and bootcamps with hands-on learning, time-tested curriculums, and education from top industry experts.
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.
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 18-hour SQL Bootcamp open to beginners, participants will discover the essentials of databases and how to write SQL code to retrieve and analyze data. Through hands-on exercises, participants learn everything from data types to basic queries and advanced topics, including aggregating and joining. Topics include SQL GUI basics, fundamental to advanced querying, table creation, joins, views, functions, and external data connections. The course is taught using PostgreSQL and applies to other relational databases, including SQL Server and MySQL. Participants can retake the course for free within one year.
Flatiron offers on-site and online courses in software engineering, data science, UX design, and cybersecurity. You’ll find they are located all over the U.S. including Austin, Chicago, Denver, Houston, New York, San Francisco, Seattle, and Washington, D.C.
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.
Thinkful aims to prepare students for the world’s fast-paced and job-competitive fields in software engineering, data science, data analytics, and design. Its course are held online, and it hosts events at its locations across the U.S. including California, Texas, Chicago, Florida, Washington, Denver, Boston, and Philadelphia.
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 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 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.
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.
General Assembly provides a variety of bootcamps and workshops in digital marketing, user experience design, and immersive courses in software engineering and data science. Students have a choice between part-time, full-time, or online classes, committed to finding you the most flexible fit for your busy schedule.
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.
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 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.
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.
NYC Data Science Academy provides data science and data engineering training with comprehensive curriculums in Python, Hadoop, Spark, R, and many more. NYC Data Science Academy offers immersive courses, bootcamps, and job training both online and in-person.
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.
This data science with Python course is for people with a basic knowledge of programming with Python. This comprehensive course will explain how to work with some of the most widely-used data analysis and visualization modules, such as Pandas, matplotlib, Numpy, Scipy, and more. The course will begin with a review of the basic syntax and data structures of Python before moving on to object-oriented programming, scientific computation, and data visualization. The final unit will teach you how to manipulate data with Pandas before you complete a final project.
Ironhack is an international tech school located on nine campuses including Miami, Madrid, Barcelona, Paris, Berlin, Amsterdam, Mexico City, Lisbon, and Sao Paulo. Ironhack offers a variety of bootcamps and immersive courses both online and onsite in web development, UX/UI design, and data analytics.
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".
Located in Washington and Singapore, Data Science Dojo offers both in-person and online data science certificates and bootcamps. Data Science Dojo provides courses in data engineering, online data science for managers, internet of things boot camp and corporate training on-site.
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.
Lambda School offers online live courses in data science, back end, and full stack in a 900-hour robust course. Similar to a 4-year degree and much more in-depth than a typical 12-week boot camp, Lamda graduates understand all aspects of computer science.
This course has five sections that cover analyzing data, building systems and predictions, and communicating insights. The first half of the course includes instruction in Statistics Fundamentals, like data wrangling and linear algebra, Predictive Modeling like linear models and data visualization, and Data Engineering with SQL, productization, and cloud. The second half teaches Machine Learning with natural language processing and neural network foundations, and Computer Science, with Python and OOP, algorithms, data structures, graphs, and hash tables.
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You have several options when it comes to learning Data Science, so we’ve chosen 156 of the best Live Online courses from the top 64 training providers to help you make your decision. But even so, with the variety of considerations including cost, duration, course format, starting level, and more, choosing the perfect course still isn’t that easy.
Here are the key questions you should ask yourself before enrolling in a Data Science course. We hope you’ll find the best option based on your learning preferences and goals.
Enrolling in the right skill level is pivotal. Skipping over prerequisites can leave you confused, while choosing a course too easy will waste your time and tuition dollars.
If you’re new to Data Science, there’s no need to fear. We’ve found 86 beginner courses, with costs ranging from $296 to $27,500. The top options open to beginners include:
Note that beginner courses still typically assume basic proficiency with computers.
Already comfortable with the basics of Data Science and feel ready to move to an intermediate or advanced class? Consider the following courses which all require some prerequisite knowledge:
Live Online training is synchronous training where participants and the instructor attend remotely. Participants learn and interact with the instructor in real-time and can ask questions and receive feedback throughout the course. Instructors can remote into students’ computers (with prior permission) to assist with class exercises and any technical issues. The courses are hands-on and interactive like in-person training.
You can attend the course from your own home or office. This option works best for those without easy access to a nearby facility, and it has become increasingly popular during COVID-19.
If you attend a virtual training from your home or office, you’ll need a computer with strong internet access and any relevant software installed prior to the course. Most schools provide setup instructions before the course, and some will provide direct assistance.
The instruction takes place via a teleconferencing software like Zoom, Webex, or GoToMeeting, and some schools have their own learning portals.
It’s crucial to find a course that fits your schedule. For live online Data Science training, we’ve found flexible scheduling options, including weekday, evening, and weekend courses.
Also note, 6 courses we’ve found require a full-time commitment. These courses are “career-changer” courses that typically span over several months and require 40 or more hours of work per week, whether in the classroom or out-of-class assignments and projects. They also typically require a large financial commitment, although many provide payment plans and financing options. Full-time courses include:
Due to changing schedules and uncertainty during COVID-19, we recommend that prospective students confirm course availability directly with the school.
With Data Science encompassing so many verticals and subtopics, it could be challenging to find what you’re looking for. We’ll help you break down the subcategories and related topics (see the Data Science topics section) to focus directly on one of the subcategories.
When learning Data Science, you can attend a course or program that dives comprehensively into Data Science, provides a brief introduction into Data Science, or focuses on a particular topic, including Python Data Science, SQL, or Machine Learning.
If you’re committed to learning Data Science comprehensively, we’ve found several courses that can help you achieve that goal.
There’s a lot to learn within Data Science, and if you’re trying to get a broad overview, a sense for the industry and job prospects, and the types of things you would learn in a Data Science course, these introductory courses are a good place to start.
Within Data Science, you can focus your learning on a specific topic, including Python Data Science, SQL, Machine Learning, Python Machine Learning, and R Programming. Each one of these topics will directly enhance, supplement, or support your learning in Data Science. To see how each topic relates to Data Science and to focus your learning on any subcategory, see the subtopics section above.
For a quick overview, here are some popular classes:
When learning Data Science, there are a variety of learning goals you can achieve, including learning Data Science comprehensively, gaining a broad introduction to Data Science, getting started, adding to existing skills, or embarking on a new career path.
To find the perfect fit for you, it’s important to determine what your training goals are. Here is a breakdown of the variety of courses and learners.
For those who are committed to comprehensively understand Data Science and ready to spend 18 hours to 162 hours to master Data Science, these classes will help achieve that goal. With prices ranging from $975 to $4,500, there is a financial commitment, but learning these skills can have a tremendous impact on job performance and earnings potential.
Learning Data Science comprehensively can be a large financial and time commitment. If you’re not committed quite yet, or just want to learn about the field or subject, these courses can give you a high-level overview to help inform larger decisions. Note that most of these courses tend to be broader and less hands-on.
If you know you need to get started in Data Science but you’re not quite committed to learning it comprehensively, these courses will get you started with hands-on skills you can use right away. Many schools offer the ability to continue learning with intermediate-to-advanced courses, and some offer package discounts. All these courses are open to beginners.
For those with some familiarity with Data Science looking to advance or add to their skills, these courses provide those with experience the perfect opportunity to skill-up. All these courses require prerequisite knowledge, and we’ve included a brief note for many of them, but you should check with the school for more details on the entry requirements.
You’re not only committed to learning Data Science comprehensively, but you’re hoping and ready to break into a new career. While securing a new career is not guaranteed, these courses provide in-depth training in Data Science. Many offer job support and some offer a money-back guarantee. Job support typically includes resume writing, help with job applications, portfolio building, and career counseling, but the services vary by provider.
Applications are typically required and many also require remote prework to build essential concepts before the more intensive “live” training. And due to the steep prices (some courses as high as $60,229) many programs provide financing options. See financing notes below but always be sure to confirm with the school and read the terms and conditions. Not all applicants are admitted and approved for financing.
Here are several “career-changer” programs. All the programs include career services (see the provider’s website for details on what is included).
Data Science is an in-demand skill that is essential for a variety of career paths. Here are some popular positions listing Data Science as a skill and the average national salaries according to Indeed as of August 2020.
See the careers section for more information about the top related careers and salaries, and visit the career pages for detail on skill requirements, day-to-day work, compensation, tips, and more.
Some benefits of live online Data Science training include:
While there are several benefits to live online training, there are a few important things to consider. You should make sure you have a quiet workplace with strong internet access. Additionally, you should have the necessary applications installed prior to class and your computer should meet any system requirements. To ensure a seamless learning experience, some schools provide remote setup support and Zoom tutorials upon request prior to the course.
Pricing for Data Science training varies by school, duration, method of delivery, and several other factors.
For live online training, prices range from $3/hour to $221/hr.
See the Data Science pricing analysis section to compare course fees.
For Data Science corporate and on-site training, contact us at (212) 226-4149 or firstname.lastname@example.org to receive a quote and free consultation. We can customize the curriculum to meet the needs of your team.
See the tuition comparison below to compare Data Science courses by cost per training hour.* For private tutoring or corporate training (onsite or virtual), contact us at email@example.com for a quote.
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Disclaimer & Notes: Hourly rates are estimates only. Courses are not available on an hourly basis. Several other factors that contribute to pricing (such as job support and free retakes) are not factored into pricing per hour. 1 day is estimated to have 6.5 hours of training; 1 week is estimated at 35 hours; and 1 month is estimated at 150 hours. Actual hours will vary by school. Course pricing is subject to change without notice, certain discounts may not be included, and pricing may vary by location.
In today’s digital ecosystem, businesses and organizations collect unimaginable amounts of data on their customers, users, clients, and constituents. In 2020,approximately 40 zettabytes of data were created (or 40 billion terabytes, roughly 50 times the amount of sand on all the world’s beaches). Every day, internet users create as much data as was created in hundreds of years of human history, and data science is the field responsible for collecting, organizing, and using this data.
Data science is a broad term that encompasses how individuals and companies gather, clean, analyze, and communicate enormous data sets to make strategic business decisions. The field of data science continues to emerge as one of the most promising and in-demand career paths for talented professionals. Many companies today have an incredible amount of data but lack the human power and tools to gather meaningful insights from that data, so there is explosive demand for data science professionals. Learning data science is one of the best ways to boost your hiring potential and start a profitable career.
Despite being a simple program most commonly associated with office workers, Microsoft Excel is vital for data science professionals. Excel spreadsheets and workbooks are used to construct and organize the basic databases that Data Scientists utilize and query. Excel also has powerful data visualization features that make it useful for communicating information to invested parties. Skill Data Scientists will constantly be building on their Excel databases using languages like SQL and Python, but knowing advanced Excel functions is an important skill for Data Scientists and Data Analysts to learn.
SQL, or Standard Querying Language, is one of the most popular programming languages for building, accessing, and querying databases. Data science relies heavily upon the ability to collect and organize huge amounts of data, far more than human beings can process, and SQL is one of the languages that make this possible. Not only does SQL help users build programs that store this data, but they can also use it to automatically query that data using complex, conditional statements and relational searches. This allows users to find information within the database that would be otherwise invisible to someone who was simply attempting to look through the data. In addition to making these queries directly, SQL is also used to create automated querying statements to help users discover new insights in their data.
Arguably, the most important skill for aspiring data science professionals to learn is Python. Python is a versatile, general-purpose programming language that is, according to TIOBE, the most widely used programming language in the world. It is used heavily in data science projects for managing and organizing data, regardless of the kind of data in question. It is also important for the computational programs that allow machines to automatically read and organize data, such as programs for scrapping user data from web browsers or online traffic. Owing to these major functions, Python is also an important programming language in the emerging field of machine learning since it powers the algorithms that allow computers to read data and interpret data without the need for a human operator.
Data isn’t particularly useful if you can’t communicate what inferences and conclusions others should draw from the data. This makes data visualization an important skill for Data Analysts and other professionals to learn. Data visualization tools help users transform raw numbers and data into visually compelling charts, graphs, and maps. Two of the most common data visualization tools are Tableau and Microsoft PowerBI, each of which provides users with the tools to automatically and dynamically update their informational graphics with new or changing data. Both programmers are designed to support non-programmers looking to visualize data, meaning that even professionals like journalists and policy advocates can benefit from learning these applications. However, if you know Python and SQL, you can write custom programs to empower these platforms to offer even more professional functionality.
One of the most common professional uses for data science skills is data analytics. Given how much data is produced daily, businesses, institutions, and other organizations are realizing how much they can gain by collecting and analyzing this data. Data analytics refers to this process wherein professionals utilize data science tools to look at things like consumer data, web traffic, demographic information, or advanced analytic metrics to draw conclusions and make recommendations based on these conclusions. Data analytics is utilized in almost every field and industry today since the programs built by Data Scientists offer an incredibly robust set of tools for gathering information. Businesses use data analytics to track consumer behavior and improve their marketing strategies, government agencies utilize data to understand demographic behaviors better and make policy recommendations, and non-profit advocacy organizations use data analytics to build more persuasive targeted campaigns. Data analytics is even used in fields like professional sports and fitness training to help athletes and coaches make quantitative decisions. No matter what field you are interested in finding work in, there is a good chance that learning how to read and analyze data can help you break into the industry.
One of the most exciting developments in data science in the last few years is the improvement in machine learning and artificial intelligence technologies. Machine learning is the process of writing algorithms and computer programs capable of ‘reading’ and interpreting data without the input of a human operator. Based on the data they have read and their internal programming, these programs produce new outputs based on the information they have ‘learned.’ Currently, the primary use of machine learning algorithms is in predictive content recommendation systems, such as the ones that recommend products and films on websites like Amazon and Netflix. However, many new versions of this technology are becoming publicly available, including elaborate chatbots and AI art programs. These technologies are still in their infancy, but they have the potential to revolutionize a wide range of industries, from marketing and consumer analytics to diagnostic medicine and digital entertainment. Anyone interested in staying on the cutting edge of modern technological developments should consider learning Python to help them build machine learning algorithms.
One of the major industries that has been radically altered by the development of data science practices and technologies is the financial industry. Bankers, Financial Analysts, and Investment Analysts all utilize data analytic programs and tools to help them better understand the movement and trends of markets and assets. Using this data, financial specialists can provide more targeted recommendations for their clients, and they can more consistently make decisions that produce solid RoIs. Given the amount of money that is moved every day in the financial sector, it is imperative that analysts have a solid understanding of the tools and techniques that are used to help them identify trends that would otherwise be invisible within the data. FinTech specialists also need to understand how financial records are kept and written so that they can get a fuller picture of the data that they are adding into their analyses (if you have bad data going into a system, you are only going to get bad results). Learning some FinTech programs can also be useful for anyone hoping to build their own investment portfolio.
While an understanding of data science is expected for many data-related career choices, there are still many other supplementary skills data analysts and data science experts need to know. Knowing this, it's important to understand which career path is best for you to better understand the amount of data science knowledge you need, as well as the other tools and programs you should explore. You should learn more about the salaries and careers you can achieve by learning data science before embarking on your new path.
Data scientists are in high demand. Knowing this skill can lead to many fulfilling career opportunities, including Machine Learning Engineer and Data Engineer. Some careers, like Machine Learning Engineer, also require knowledge of artificial intelligence and deep learning and some soft skills like communicating your models to those with little technical expertise. For positions like those, you’ll need subject-specific training and an understanding of many important machine-learning concepts and terms.
With live online data science training, you can learn this high-demand skill from anywhere. You’ll interact with the instructors in real time and work on various hands-on projects. The cohort style of live online training also helps students to stay engaged and on track to complete the course. Students enrolled in live online classes will be able to receive personalized, real-time feedback from their instructors, which can be vital for students’ success. Students can even permit their instructors to interact directly with their devices remotely and guide them through difficult data science concepts. Once you have a firm understanding of data science, you’ll be able to start working on an impressive range of data-related projects.
Several schools, including Noble Desktop, the provider of this tool, offer live interactive data science courses to help you meet your goals. For those interested in learning Python and Python’s many data science applications, Noble offers a Python for Data Science bootcamp taught by experienced professionals that covers many introductory programming concepts like loops, functions, and objects, as well as many common advanced data science concepts. In this class, students will learn the basics of using Python to wrangle, organize, and query data. They will also learn how to use Python libraries to create graphs and visualizations that communicate the content of this data. This wonderful introductory course offers students of all skill levels a way to start their data science training.
Noble also offers longer courses and comprehensive certificate programs catering to students with different interests, including a Python for Data Science & Machine Learning Bootcamp. This course not only covers the basics of Python programming but also explores various Python libraries, how to apply machine learning algorithms to data, data visualization, and other advanced skills. Students will learn how to write machine learning algorithms and how to train those algorithms so that the interpretations the machine makes are accurate, unbiased, and applicable to real-world problems. Like all Noble classes, it includes a free retake and a guarantee that you’ll learn the skills covered in the syllabus, subject to terms and conditions.
If you want to enter a career in data science, check out Noble’s Data Science Certificate program, which provides a comprehensive overview of the most important data science tools and concepts. The Data Science Certificate program introduces students to the field of data science and is heavily focused on utilizing Python for data science, but it also explores SQL applications and other concepts to help provide students with a deeper understanding of data science. This bootcamp is broken into four subject-specific units, so it is manageable and accommodating for those with busy schedules. For more details, check out theFAQ.
All of Noble’s courses come with a free retake option within one year, and the career-focused bootcamps, including the Data Science Certificate program, offer students professional development services to help ensure that they are ready for the job search. These professional development programs include focused portfolio-building seminars and one-on-one career mentorship sessions during which students can receive personalized assistance on any aspect of their job search process (from searching for jobs to writing cover letters to preparing for interviews).
Other schools, including Flatiron School, Metis, Thinkful, General Assembly, and others offer a variety of courses and bootcamps. Much like Noble Desktop, these schools offer their courses both in-person and online and are taught by industry experts. These other schools also offer short subject-specific courses as well as longer-form bootcamps, to best meet the needs of students. Since data science is such a wide and varied field, students have a range of options available to them in terms of the content and schedule of an online data science course. To learn more about the optison available, consider exploring your options for live online data science classes using Noble Desktop’s Classes Near Me tool.
For example, Flatiron School offers a comprehensive yet beginner-friendly Data Science Bootcamp that provides students with a comprehensive look at many important data science tools and concepts, including working with SQL and Python, running regression analysis, A/B testing, machine learning, and natural language processing. This course offers robust, career-focused instruction and aims to prepare students for a wide range of data science careers. This project’s capstone instruction emphasizes advanced machine learning algorithm programming.
Thinkful offers full-time and flexible part-time scheduling options for its Data Science Bootcamp. This is a beginner-friendly, career-focused course that aims to provide students with an immersive overview of the key concepts in data science. Students will learn the basics of programming with Python, SQL, and their important data science libraries. Then, students will build on these skills through guided, hands-on machine learning instruction. This course aims to provide students with the instruction that they need to begin work as Data Scientists or Data Analytics specialists.
Students with a computer science or data analytics background may want to enroll in a more specialized training program. For example, General Assembly offers a Python and Machine Learning Bootcamp for students seeking training in machine learning practices. The course teaches students how to use Python to collect data from large datasets and internet traffic, and students will learn how to feed this data to a machine learning algorithm to start analyzing the data they’ve collected. This class is a good fit for students who are looking to learn a specific skill set that they can use to complement their existing knowledge.
Similarly, students may be interested in enrolling in a more focused career training class, like NYC Data Academy’s Data Science with Python: Data Analysis and Visualization class. In this course, students will learn how to apply data science and Python programming skills to practical data analysis tasks and exercises. They will learn the basics of programming with Python and receive guided instruction in using that Python knowledge to query, organize, and analyze data. Once students are comfortable with Python programming, they will learn how to use Matlib and Seaborn for visualizing data and producing evocative graphs and charts. This practical training is ideal for students looking to become data analysis professionals.
Other focused training programs aim to teach students how to apply their data science skills to specific professional fields. For example, Data Science Dojo offers a Data Science for Business Leaders course that teaches students how to use Python programming and other data analytics training in team management and business analysis. Courses such as these are ideal for students who know the field they want to pursue and build a robust skill set in that specific job role. Students enrolled in these courses will learn general-purpose data science skills, but they will be targeted at applying those skills to providing business management solutions.
Students who aren’t confident that they want to pursue a career in data science may want to take an introductory course, such as Byte Academy’s Intro to Data Science program. In courses like this, students will receive accelerated training in the foundational principles of data science, including coding with Python and SQL and database management. These courses tend to be designed with beginners in mind, making them good places to start for students without a computer science background. Students enrolled in these courses will need additional training to become professional Data Scientists, but they will still receive targeted data science training that they can apply to additional skills training.
Students looking for an introductory course can also enroll in a program like Code Fellows Intro to Data Structures and Algorithms course. This course provides students with an introduction to working with data algorithms, particularly in the planning phase. This course teaches students how to work with data arrays, plan programming tasks, and learn important computer science concepts and vocabularies. This course aims to prepare students for practical interviewing skills, emphasizing teaching students how to demonstrate their proficiency with data-related concepts.
Finally, for students who aren’t entirely certain that data science is the field that they want to pursue, enrolling in a course like ONLC Training Center’s Python Programming Level 1: Introduction for Non-Programmers course is a good way to learn computer science skills while keeping your options open for additional data science training. Courses such as this one aim to teach students to be comfortable with the basic programming process with Python so that they can be prepared for more advanced data science training should they wish to continue their education. These classes are an ideal fit for students looking to learn computer science but unsure that they want to apply their Python programming skills to a data science career. These classes are also more flexible regarding scheduling since there isn’t a long-term commitment to the course.
Since data science is such a broad skill applicable across many roles and industries, you’ll want to be sure that you choose a course that meets your goals, whether you’re aiming to advance in your career or trying to learn the basics for your first data science position. So when choosing a live online data science course, you’ll want to focus on the industry focus, job function, and course duration.
Data science training provides an invaluable asset to companies that work with data on an advanced level and use it to drive business decisions. Being able to read, interpret, and analyze data is a vital skill in virtually every professional industry and companies that ignore this data are leaving profits on the table. For companies looking to train their employees, virtual training is available through Noble Desktop. You can send participants to regularly scheduled group classes held virtually or schedule a private session for your team. Instructors can conduct the training for beginners to advanced users and customize the lesson plan to fit the needs of your team. Employers who are looking to provide alternative training options can also purchase discounted vouchers to let their employees sign-up for any of Noble Desktop’s open-enrollment data science classes. For more information about corporate training for your business, please email firstname.lastname@example.org.
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