Classes are running in-person (socially distanced) and live online. Secure your seat today

Noble Desktop Noble Desktop
  • Coding
    • Web Development
    • Python
    • JavaScript
    • FinTech
    • SQL
    • High School Coding
    • iOS Development
    • Data Science
    • Web Certificates
    • HTML Email
    • WordPress
    • Machine Learning
    • React
    • Cybersecurity
    • All Coding Classes & Bootcamps
  • Design
    • Graphic Design
    • Web Design
    • Photoshop
    • After Effects
    • Premiere Pro
    • InDesign
    • Illustrator
    • Creative Cloud
    • Video Editing
    • Motion Graphics
    • Visual Design
    • UX Design
    • Figma
    • Sketch
    • Adobe XD
    • AutoCAD
    • All Design Classes & Certificates
  • Business
    • Digital Marketing
    • SEO
    • Google Analytics
    • Google Ads
    • Social Media
    • Data Analytics
    • Excel
    • Tableau
    • PowerPoint
    • Financial Modeling
    • Finance
    • Project Management
    • All Business Classes & Certificates
  • Certificates
    • Graphic Design
    • Motion Graphics
    • UX & UI Design
    • Web Design
    • Social Media
    • Digital Marketing
    • UI Design
    • Digital Design
    • Video Editing
    • Data Analytics
    • Full-Stack Web
    • Front-End Web
    • JavaScript Development
    • Software Engineering
    • Python Developer
    • FinTech
    • Cybersecurity
    • Data Science
    • Find & Compare Certificates by Topic
  • Corporate
    • Social Media Marketing
    • Excel
    • SQL
    • Python
    • Data Science
    • Graphic Design
    • Web Design
    • Photoshop
    • After Effects
    • Video Editing
    • Digital Marketing
    • Data Analytics
    • Adobe
    • Microsoft Office
    • Project Management
  • Compare
  • Schedule
  • Coding
    • Web Development
    • Python
    • JavaScript
    • FinTech
    • SQL
    • High School Coding
    • iOS Development
    • Data Science
    • Web Certificates
    • HTML Email
    • WordPress
    • Machine Learning
    • React
    • Cybersecurity
    • All Coding Classes & Bootcamps
  • Design
    • Graphic Design
    • Web Design
    • Photoshop
    • After Effects
    • Premiere Pro
    • InDesign
    • Illustrator
    • Creative Cloud
    • Video Editing
    • Motion Graphics
    • Visual Design
    • UX Design
    • Figma
    • Sketch
    • Adobe XD
    • AutoCAD
    • All Design Classes & Certificates
  • Business
    • Digital Marketing
    • SEO
    • Google Analytics
    • Google Ads
    • Social Media
    • Data Analytics
    • Excel
    • Tableau
    • PowerPoint
    • Financial Modeling
    • Finance
    • Project Management
    • All Business Classes & Certificates
  • Certificates
    • Graphic Design
    • Motion Graphics
    • UX & UI Design
    • Web Design
    • Social Media
    • Digital Marketing
    • UI Design
    • Digital Design
    • Video Editing
    • Data Analytics
    • Full-Stack Web
    • Front-End Web
    • JavaScript Development
    • Software Engineering
    • Python Developer
    • FinTech
    • Cybersecurity
    • Data Science
    • Find & Compare Certificates by Topic
  • Corporate Training
    • Social Media Marketing
    • Excel
    • SQL
    • Python
    • Data Science
    • Graphic Design
    • Web Design
    • Photoshop
    • After Effects
    • Video Editing
    • Digital Marketing
    • Data Analytics
    • Adobe
    • Microsoft Office
    • Project Management
    • All Corporate Training
More
  • Compare
  • Schedule
  • Classes Near Me
  • FAQ
  • Blog
  • Workbooks
  • Free Seminars
  • High School Classes
  • Resources
  • Student Testimonials
  • Student Showcase
  • Job Board
  • Evaluation
  • Course Catalog
  • Instructors
  • Veterans

Contact Us

  • (212) 226-4149
  • hello@nobledesktop.com

Data Science Classes in NYC or Live Online

Hands-on Training from Experts Small class sizes

Become a Data Scientist with Courses & Certificate Programs

  • Featured
  • Data Science
  • Data Analytics
  • Corporate Training
  • Why Noble
  • About Data Science
  • Careers
  • Campus & Live Online
  • Learning Resources
  • Upcoming Classes

Which Data Science Class is Right for You?

Earn a certificate in data science in our full or part-time programs. Our courses are taught and developed by top data scientists in New York and are open to students with no programming experience.

  • Data Analytics Certificate

    • Weeknights or weekdays
    • 156 hours
    • Open to beginners
    • Financing available
    • 1:1 Mentoring

    Learn the skills you’ll need to become a Data Analyst or Business Analyst, including data analysis, visualization, statistical analysis, and how to work with relational databases. Build a portfolio of projects and prepare for a career.

    View course
  • Data Science Certificate

    • Weekdays, weekends, or weeknights
    • 114 hours
    • Open to beginners
    • Financing available
    • 1:1 Mentoring

    Master the tools to become a data scientist: Python, SQL, automation, and machine learning. Learn Python programming fundamentals and analyze data with Pandas, NumPy, and Matplotlib, and query databases with SQL. Use machine learning to apply regressions and other statistical analysis to create predictive models.

    View course
  • Python Data Science & Machine Learning Bootcamp

    • Weekends, weekdays, or weeknights
    • 96 hours
    • Open to beginners
    • Payment plan available
    • 1:1 Mentoring

    Learn Python programming fundamentals and analyze data with Pandas, NumPy, and Matplotlib. Use machine learning to apply regressions and other statistical analyses to create predictive models. Create dynamic dashboards and other data visualizations.

    View course
  • FinTech Bootcamp

    • Weekdays, weekends, or weeknights
    • 114 hours
    • Open to beginners
    • Financing available
    • 1:1 Mentoring

    Gain the analytical and programming skills to break into finance technology. Learn the fundamentals of Python programming, data science, financial analysis, data visualization, and machine learning. Create your own final project.

    View course
  • Python for Data Science Bootcamp

    • Weekends, weekdays, or weeknights
    • 30 hours
    • Open to beginners

    Pick up Python fundamentals and quickly transition into analyzing real-world datasets. You will learn to how to clean and combine data, as well as generate useful statistics and visualizations. The final sessions will be focused on using linear regression to extrapolate from data and make predictions.

    View course
  • Python Machine Learning Bootcamp

    • Weeknights, weekdays, or weekends
    • 30 hours
    • Prerequisites required

    Take a step beyond normal programming, into using algorithms that can independently learn patterns and make decisions. Machine learning skills are in high demand, as these algorithms now run the majority of trading on Wall Street and the product recommendations at big companies like Amazon, Spotify, and Netflix.

    View course
  • 45,000+
    Students
  • 33
    Years
  • 2,500+
    Testimonials

Data Science Courses

Master in-demand programming languages, including Python and SQL, to analyze data, query databases, and create predictive models.

  • SQL Bootcamp

    • Weekdays, weeknights, or weekends
    • 18 hours
    • Open to beginners

    Learn to extract info from databases by writing SQL queries, joining tables, aggregating data, and filtering results. You’ll learn PostgreSQL in this class, but the concepts apply equally to other databases such as SQL Server and MySQL

    View course
  • SQL Server Bootcamp

    • Weekdays or weekends
    • 20 hours
    • Open to beginners

    Learn to extract information from databases by writing SQL queries, joining tables, aggregating data, and filtering results so you can turn data into actionable insights.

    View course
  • FinTech Bootcamp

    • Weekdays, weekends, or weeknights
    • 114 hours
    • Open to beginners
    • Financing available
    • 1:1 Mentoring

    Gain the analytical and programming skills to break into finance technology. Learn the fundamentals of Python programming, data science, financial analysis, data visualization, and machine learning. Create your own final project.

    View course
  • Python Data Visualization & Interactive Dashboards

    • Weekdays, weekends, or weeknights
    • 30 hours
    • Prerequisites required

    Manipulate and visualize data in this hands-on course, where you'll learn about data stories, dashboard design and Python's most important data visualization libraries.

    View course
  • Python for Automation

    • Weeknights, weekdays, or weekends
    • 6 hours
    • Prerequisites required

    Learn Python to extract data from websites. Along the way, you’ll learn how to write loops so that your web scraping code can process a large number of pages.

    View course
  • Data Analytics with R Bootcamp

    • Weekdays only
    • 30 hours
    • Open to beginners

    Visualize data with the R programming language in this immersive data analytics bootcamp.

    View course
See All Data Science Courses

Learn the Skills Guarantee™

Learn the concepts and skills covered in these courses or your tuition is on us. See details and terms & conditions.

Learn the Skills Guarantee logo

Hands-on training

Work on projects proven to boost retention

Students in class

Time-tested curriculum

Refined over many cohorts for an optimal learning experience

The teaching method at Noble Desktop is perfect and the classes provide you with infinite knowledge that makes you eager to take everything they offer. I love Noble!
—Ivonne Ackerman

Student reading workbook

Learn from experts

Experienced educators who are driven to help you succeed

Retake for free

Refresh the materials for free within one year

Data Analytics Courses

Analyze, summarize, and visualize data with Excel, SQL, and Tableau. Master the tools you need to succeed as a data analyst.

  • Data Analytics Certificate

    • Weeknights or weekdays
    • 156 hours
    • Open to beginners
    • Financing available
    • 1:1 Mentoring

    Learn the skills you’ll need to become a Data Analyst or Business Analyst, including data analysis, visualization, statistical analysis, and how to work with relational databases. Build a portfolio of projects and prepare for a career.

    View course
  • Data Analytics Technologies Bootcamp

    • Weekdays only
    • 57 hours
    • Open to beginners
    • Payment plan available

    Learn the industry-standard tools for data analytics: Excel, SQL, and Tableau. Organize, analyze, summarize, and visualize your data to present actionable insights.

    View course
  • Tableau Bootcamp

    • Weekdays or weeknights
    • 12 hours
    • Open to beginners

    Tableau is a powerful tool, giving you full control of the look and feel of your visualizations, and helping compile your charts in the form of stories and dashboards. 

    View course
  • Data Analytics Foundations

    • Weekdays or weeknights
    • 12 hours
    • Open to beginners

    Learn the fundamentals of data analytics in this beginner-friendly class. Find out how Data Analysts and Business Analysts use analytics and statistical modeling for problem-solving, decision-making, and forecasting.

    View course
  • Excel for Data Analytics

    • Weeknights or weekdays
    • 18 hours
    • Prerequisites required

    Learn the Excel skills you'll need to perform common types of data analysis. Learn Pivot Tables, VLOOKUP, Sort & Filter, and advanced functions, as well as techniques to speed up your workflow.

    View course
  • SQL Bootcamp

    • Weekdays, weeknights, or weekends
    • 18 hours
    • Open to beginners

    Learn to extract info from databases by writing SQL queries, joining tables, aggregating data, and filtering results. You’ll learn PostgreSQL in this class, but the concepts apply equally to other databases such as SQL Server and MySQL

    View course
See All Data Analytics Courses

Corporate & Onsite Training

Help your team harness the power of big data. Create a custom training program at your location or ours, or send employees to our regularly-scheduled group classes.

Request more info: hello@nobledesktop.com

Data Science

Use the power of Python and R to automate tasks and make informed data driven predictions.

Databases

Harness the power of SQL to extract, summarize, and analyze data.

Data Analytics

Train your employees in Excel & VBA to increase productivity in day-to-day work.

Data Visualization

Use data visualization tools Tableau and Power BI to create intelligent and easy-to-read charts.

Machine Learning

Create machine learning algorithms and models to predict outcomes.

Automation

Write scripts to automate everyday tasks.

Private Training

  • Available onsite at your location
  • Modern computer labs available at our offices
  • Customize or choose from our existing courses
  • Free instructor consultations to finalize content
Or

Group Class Vouchers

  • Send employees to our group classes
  • Extensive offerings and flexible scheduling
  • Simple billing and logistics
  • Computers and training resources provided

We’ve trained thousands of companies!
Let us create the perfect program for your team.

hello@nobledesktop.com (212) 226-4149

Why Learn at Noble

Launch your career as a data scientist or analyst. Our modular approach makes learning more affordable and easy to build on. You can start with our introductory Python and SQL courses and earn a certificate over time. You only take the classes you need to increase your earning potential, gain in-demand skills, and embark on a career in a new line of work!

  • Students learning graphic design & coding at Noble Desktop

    Learn Real-World Design & Coding Skills

    “Noble Desktop is far and away the most efficient way of gaining computer graphics skills. They give real-world exercises to work on, teach best practices, and inspire many an ‘aha!’ moment. Highly recommended.”
    Joanne Hu

  • Students learning hands-on at Noble Desktop

    30 Years of Experience

    Since 1990 we have perfected the craft of teaching. If students get hung up on an issue, we tweak the class to make it better. We’re the longest running independent training center for code and design in NYC.

Highly Reviewed by Our Alumni

From our hands-on training style to world-class instructors and proprietary curriculum, we deliver a learning experience our alumni can be proud of.

Yelp
Google
Switchup.org

Our Data Science Classes are rated 4.7 stars by 538 students

in the past 24 months

It was great to see my progress during the duration of this bootcamp. I started with no prior knowledge of Python and by the end of the course, I was able to complete a machine learning project using Python.

Niekel Griffith

This was easily the best instruction I have received all year -- I honestly feel like 3 days was enough time to get the entirety of Python's basics down, and I am looking forward to actively pursuing this as a data language. Boris was a fantastic teacher with excellent pacing and an easy-to-understand style, and the class materials were laid out in a sensible manner to pack a lot of content into a few short days of instruction.

Zachary Rusconi

Matt was awesome. He's knowledgeable, thorough, easy to understand, and laid-back enough to keep me from feeling overwhelmed by the amount of material he was covering! He's also great at helping students troubleshoot, so that they understand exactly where they may have gone wrong in an exercise. This was critical for me to truly understand what I was doing, so I'll know what to do once I'm on my own.

Mindy Carpenter

Great class! There was a good balance of lecture and practice. The exercises were fun and really helped me practice the skills learned in the lecture portion. Ethan was a great instructor too!

Elizabeth Fahey
Canon USA

The instructors are top notch; very approachable and they know their stuff. Their class format is see and do; they explain an exercise step by step then have you complete it and are there to help you if you get stuck. I found the hands-on approach very effective. The exercises are modular and build on previous ones and every time you complete one you've made something happen that you didn't know how to do 30 minutes ago. That's a great feeling and helps keep you engaged in what you're learning. Piece by piece you're building practical skills that you can apply immediately.

Jonathon Powell

Great way to start learning Python!

Nolan Young

Enrolling in the Python for Data Science course was the best decision I could have made for myself and my advancing career. I'm feeling confident enough to move beyond my traditional role using what I've learned at Noble Desktop to create a portfolio of my knowledge.

Aja Walton

Really great way to jump into a complicated topic.

Nolan Young

I highly recommend this class to anyone that is looking for an intro to machine learning.

Marcelo Zampietro

Rob is extremely knowledgeable and made learning a complicated subject matter more accessible

Jason Alter
Tapestry Inc.

Noble is the best. Period.

Andrew Ortiz
JP Morgan Chase

I feel very comfortable with the Python syntax after taking this course...I had zero previous experience.

Philip E Camp
FEMA

Highly recommended course and the instructor is detail oriented and knowledgeable!

Yamini Y
American Express

A strong dive in SQL. You'll walk out of this class with a good grasp of database handling. A great professional skill.

Anderson Wang

Professional, supportive, engaging and down to earth instructors. Noble Desktop is always there for you.

Mai Amouyal

If you're truly starting with just about zero programming experience this particular Bootcamp will catapult you into intermediate within a few short weeks. Before the class was over I was already able to complete projects on Coursera's project series with relative ease. To be able to cover loops, numpy, pandas, and even data visualization in a short time is very impressive.

Tyler Irwin
New York Life

EXCELLENT! I was surprised by just how 'inspiring' Patrick turned out to be. He made the material interesting and provided a model of how to establish a good mind-frame necessary to mastery. I loved it. Felt like I got personal direction as well as technical skill.

Sean Kerr

Thalo is a great machine learning instructor. He takes his time to make sure you have good notes and explains everything so that you are not left behind.

Mayhugh Davis

As an experienced analyst looking to expand my skillset to include Python, this class was ideal. Without having any Python experience I am now confident I can start leveraging it in my day-to-day work. The class covers everything from how to install and access Python, to data manipulation and visualization.

Harry S Vanderburg
ABILITY Network

This is a great crash course for anyone who's worked with basic Python files and wants to know what they're reading, and to start writing scripts of their own.

Gabe Scelta
United Nations

In just one week, I went from knowing nothing about Python to being able to code in numerous ways. This virtual course did a wonderful job feeling like an in-person course and we had an engaging teacher.

Merianne Spencer

Instructors at Noble Desktop are devoted to their students!

Andrew Gordon

I highly recommend the Python for Data Science Bootcamp to anyone who has little programming experience and would like to know some basic knowledge about Python.

Yulei He
Centers for Disease Control and Prevention

Terrific curriculum and content, and a world-class instructor and hands-on practice. Couldn't have asked for a better overall experience. 10 stars out of 5!

Jordan Fogel

Had a great experience and learned a lot within such a short period of time.

Russel Rouf

Very useful instructors and good content. Would recommend the Python for Data Science Bootcamp.

Roberta Caselli

Very useful instructors and good content. Would recommend the Python Machine Learning Bootcamp.

Roberta Caselli

A fast-paced bootcamp that kept me engaged and was kept lively with humor.

Robert McLoughlin

Genghis was AMAZING. He was so clear in his explanations, and especially helpful if you had a specific question. I am in an online bootcamp now and his instruction was fantastic and helped me tremendously. Great format to offer practice SQL exercises, and then review with the instructor.

Tracy D.

Art Yudin is a fantastic instructor. During the course, he was very helpful with providing links, explaining certain methods, and providing really good examples.

Emil M.

Excellent materials and quality of instruction. I came away feeling confident in what I knew and with lots of detailed notes that I could refer to in the future. Probably the best virtual instruction that I've attended!

Leron Culbreath

I thought the content for the class provided good coverage of the foundations of Python. Art is a good instructor. I like his approach of teaching a concept, then giving us an exercise to work through.

Michael M.

Art was an awesome instructor. For someone who has no experience with Python or coding, he made it very simple to understand and took the time to make sure we were caught up to speed every few minutes. Definitely interested in learning more and looking forward to how I can apply the information I learned today, and help my team/company. Also motivated to learn more and practice this more and more.

Ben G.

I've taken a number of Python introductory courses, but this one left me feeling the most prepared to start practicing on my own. Looking forward to doing more than just 2+2!

Sean McNelis

Instructor was very good. Clearly walked through a broad amount of Python material in a succinct and helpful way.

Peter B.

Art was very knowledgeable, with great, repetitive, and helpful examples/exercises. We went through a lot of examples but the breaks and lunch breaks in between really helped to ensure we stay engaged.

Bo H.

Very solid information, a great basic Python course. Art did a great job getting the class up to speed and helping us catch up quickly if we fell behind any.

Christopher S.

Excellent. Art fine-tunes his teaching style to our level of understanding. Efficient, patient, current examples of data topics, overall great for me as a beginner - never coded at all prior!

Michelle Moreno

Art is a very helpful and patient instructor. I'm amazed at what I can build now.

Daniel Laserna

The 5-day Python bootcamp was excellent! It was exactly what I needed to get a broad overview of Python, and it got me excited to continue coding. The course instructor Brian was fantastic. He kept the class fun, interesting, and engaging. I really enjoyed his teaching style.

Rasia Naidoo

I was skeptical about whether to join these classes since I don't have any previous experience in any coding or programming languages. But the classes are appropriate for any beginner and make understanding and learning skills easy.

Anwesh Kumar Yeddula Sobitha

The teacher really cared and was enthusiastic, I'm glad I took the course. The prepared Python files are really nice. Having a "start" and "finish" version is also really nice. Can't stress enough how great it is to have extra exercise files directly related to what we covered but going in more depth than we have time for to work on afterward.

Chris Greene

This was my first experience with HTML database extraction and web scraping. Art was attentive as always and ready to explain details. I liked the fact that he always asked. "Does anyone have a question?" It is amazing how patient Art is about repeating parts of his class. Thumbs up for that!

Nikola Janjic

Art did an excellent job of helping us to understand Python!

Loyce Laurent

Art is a great instructor. He can not only explain everything clearly but also motivate us to study. A huge amount of information in such a short time. After this course, I realized how many possibilities Python opens. Even if I decided not to work in data science, I still would not regret that I took the course.

Lidiia Nikolaeva

Demystifying Data Science

The term “data science” is used in a variety of fields and disciplines. But what exactly is it?

In simple terms, data science is exactly what it sounds like: the science of using data to obtain information, and, ideally, to make decisions based on the data that was obtained. In many industries, the goal of using data science is to make strategic decisions, or to create innovative products that solve frustrating problems. After all, why collect data if you aren’t going to do anything with it?

Let’s look at a simple example.

Predicting market trends is one of the most difficult things a financial analyst can do. After all, share prices can be volatile and the market can change rapidly based on a variety of economic and psychological factors.

What if we could use data science and machine learning to make more accurate predictions based on existing data and current market trends?

With Python, we can use linear regression to predict share prices for the next thirty days, using libraries and packages like Matplotlib to create visual representations of this data. We can scrape existing data from the S&P 500 using the Google Finance API, import and manipulate this data, and make strategic decisions regarding share prices and other market-related trends.

Data science has the potential to revolutionize the way we do business. Whether we are trying to predict stock prices, analyze political data ahead of the next election, or look at years worth of health data to determine whether to adjust health insurance premiums, there is no question that data plays a crucial role in how we create, market, and deliver products.

In addition, analyzing massive amounts of data can help companies create innovative and purposeful marketing strategies. Marketing costs a lot of money, so it’s in a company’s best interest to make informed decisions about which products to market to whom, and where to invest their marketing budget. Data science takes the guesswork out of this.

What do data scientists do?

A skilled data scientist could develop algorithms that predict market trends based on a company’s prior performance in the stock market, helping financial analysts make strategic short-term and long-term decisions.

Likewise, a skilled data scientist could analyze millions or billions of pieces of data to help an insurance company make informed choices about spending, to identify potential instances of fraud, to help developers optimize the company’s user interface, to guide marketing decisions, and to identify company-wide opportunities for improvement.

Data scientists are skilled at statistical analysis, interpreting huge amounts of quantitative and qualitative data, creating machine learning tools for companies, and programming—usually in Python.

But why exactly is programming a necessary component of data science?

Data scientists need to obtain data from local files or from remote databases or they will have nothing to work with! Unlike the kinds of data analysis that we might do on a small scale (such as reviewing how much money a small business spends on X each year), which we can do easily with Excel, data scientists work with thousands or millions of pieces of data at a time.

This data comes from a variety of sources and databases, and must be aggregated, cleaned, and analyzed so that it can be used to make strategic decisions and accurate predictions. In these cases, it’s necessary to use some form of scientific computing to analyze and create visualizations of this data.

What’s the difference between data science and data analytics? What is machine learning?

Data science and data analytics are similar fields, but data science is actually an umbrella term that encompasses data analytics, machine learning, and several other data-related disciplines.

A data analyst is someone who can perform basic data visualization, statistical analysis, and draw conclusions from data sets. A data scientist goes a few steps further and handles complex data visualization and modeling, data cleaning, and extensive analysis.

Machine learning is an important component of data science. With machine learning, algorithms are used to analyze data and to predict market trends. A data scientist is generally skilled with both machine learning and data analytics. A machine learning expert is generally skilled at data science, but might have a special aptitude for probability, statistics, and programming in multiple languages.

Overall, data science, machine learning, and data analytics require many of the same skills, but the practical application of each specialty differs a bit.

Languages Used For Data Science

Python

Python is the most commonly used programming language in data science—with almost 70% of data scientists reporting that they use it—for a few reasons:

  • Python is a general-purpose programming language.
  • Python is easier to read and write than most other general-purpose languages, especially for analytical computing and quantitative data analysis.
  • Python is open sourced, and has many extensive libraries that were specifically designed for use in data science.
  • Python has numerous libraries and packages available for data science.

It surpassed R for the number one spot and has maintained this position due to its ease of use, powerful libraries and packages, clear and user-friendly documentation, and abundant community support.

Data scientists are already handling complex analysis of data, so they don’t need their programming language to be complicated, too. Python is known for its simple syntax and ease of use—even for beginners.

While some other languages (like Ruby) have clean and simple syntaxes, they don’t offer the same variety of scientific computing and machine learning libraries as Python.

Our Python classes and Python bootcamps will help get started with programming fundamentals and data science projects.

SQL

Approximately 40% of data scientists report using SQL, too.

SQL is a non-procedural language—that is, it cannot be used to write entire applications. SQL facilitates communication with databases and allows data scientists to access, edit, and re-organize pieces of data. Many Python packages and libraries work with SQL. Since SQL is not a general-purpose programming language and won’t be used on its own, Python and SQL are often used together.

R

For statistical analysis, R has a set of tools that is unmatched in depth and sophistication. Statisticians and other academics have been contributing to R for over 25 years, guaranteeing that for any statistical technique you can think of there will be a high-quality tool ready and waiting. If you have a background in statistics, you may find R easier to use because the terminology will be consistent with your training. However, since R is a specialized tool for statistical analysis, you may want to consider a more general-purpose language like Python if your interests are broader.

What Are Libraries and Packages?

One thing that sets Python apart from other general-purpose programming languages is the sheer quantity of libraries and packages available for data science. There are thousands of libraries in the Python Package Index, which makes Python a desirable choice for data scientists.

Some of the most useful libraries and packages are Pandas, NumPy, Matplotlib, and Sci-Kit Learn.

NumPy

NumPy is a powerful linear algebra package for Python. It is primarily used for scientific computing. Many other libraries (Pandas, Matplotlib, and Sci-Kit Learn, for example) are dependent on NumPy. NumPy has extensive documentation and can be installed quickly and easily.

NumPy works with multi-dimensional arrays in Python. Lists can be converted into arrays, random arrays can be created, and numerous operations can be performed on these arrays. This is a crucial feature because operations (addition, subtraction, multiplication, and division, for example) cannot be performed on standalone Python lists, but they can easily be performed on NumPy arrays. Since data scientists often need to perform operations on data sets, NumPy is an invaluable tool.

NumPy allows you to find the min, max, standard deviation, and variance on an array. It allows you to combine different arrays to form a single array.

Overall, NumPy arrays are faster, easier to use, and use less memory than Python lists. When working with massive data sets, convenience and ease of use are two big selling points.

Because arbitrary data types can be defined with NumPy, the package is able to connect with a variety of different databases. This adds to its versatility and makes it an important component of any data scientist’s technical repertoire.

Pandas

Pandas is an open-source library that provides high-performing, user-friendly data analysis tools for Python. It is one of the most popular libraries and, as such, has excellent documentation.

Pandas essentially takes data (from a CSV file or a SQL database, for example) and creates a Python object called a data frame. A data frame organizes data in a format that resembles a table, so it is easy to read, easy to analyze, and easy to work with.

Pandas is dependent on NumPy, and can optionally be used with Matplotlib for data plotting and visualization. Because of this, it can be installed on its own, or it can be installed through a package like Anacondas, which will install all required dependencies.

Pandas is usually used in one of three ways:

  • To convert a list, dictionary, or array into a data frame
  • To open a local CSV file or a related data file
  • To open a remote file (CSV, JSON, SQL database, etc.)

After opening the file that you’d like to work with, you can perform a number of different commands to analyze the data. You can perform statistical analysis (mean, median, standard deviation, and so on), you can retrieve specific data points, and you can file, sort, or group data as you see fit.

Another important feature is the ability to clean data by checking for null values within the data set. It is difficult to work with data that has not been cleaned; unintentional null values within data sets can skew your results or make the results difficult to analyze. Pandas addresses this concern by identifying pieces of data that might be missing, incomplete, or otherwise incorrect so that you can get the most accurate results from your analysis.

Matplotlib

Matplotlib is another popular library that allows data scientists to visualize data. Data visualization is a crucial step in making data accessible. It allows you to identify outliers and patterns quickly, while making data interpretation easier overall. Research shows that people, in general, are very receptive to visual representations of data, making Matplotlib an invaluable resource in data science.

Matplotlib is free, easy to install, and has robust features. Data can be rendered as a histogram, a pie chart, a line graph, a box plot, and so on. There are enough features to satisfy advanced users, but even entry-level users can create powerful visualizations of data.

Consider an enormous data set that encompasses countless data points over a long period of time. While this data can be displayed in an array or in another numerical format, it would take a while to read and analyze. There is a potential for human error when manually reading and interpreting massive lists of data. Naturally, human error is something that data scientists try to avoid.

Matplotlib allows you to choose the specific data that you’d like to work with and arrange it in any visual format that you can imagine. Data can be rendered and displayed in almost any format with a few quick commands. Because Matplotlib is so easy to use and works seamlessly with other Python libraries and packages, it is a top choice for data scientists who use Python.

Sci-Kit Learn

Many data scientists begin their analysis and evaluation of data with Pandas before moving over to Sci-Kit Learn for machine learning. Sci-Kit Learn is a machine learning library for Python that works with NumPy arrays and focuses on modeling data, not operating on it (NumPy and Pandas handle this).

Some modeling options include clustering, data sets, parameter tuning, and cross-validation. Sci-Kit Learn comes with standard data sets (for classification and regression of data, for example). Sci-Kit Learn is used in conjunction with stats and linear regression to make predictions based on inputted data sets.

Other Libraries and Packages

These libraries and packages, among others, are one of the main reasons that Python is so popular in data science. The options to import, manipulate, operate on, clean up, visualize and model data are unmatched by any other programming language’s libraries.

In our data science courses, we cover Python in-depth, and we hone in on NumPy, Pandas, Matplotlib, and Sci-Kit Learn to help you make the most of your data.

What is big data? What is small data?

In data science, big data is often defined by the 3 Vs: volume, variety, and velocity. Big data is usually tremendous in volume, full of a variety of different data types, and slower to process than small data. Big data is rich with insights, but it is not always accessible due to the sheer amount of analytics that must be performed in order to obtain the most usable information from the data set.

Small data is exactly what it sounds like -- a smaller subset of useful data, often derived from big data. Small data is organized and visualized in a way that is accessible and understandable so that we can make the most of our analysis. Anything that can be processed in Excel is considered small data.

There is a place for both big and small data in data science. It takes time and skill to process big data and to derive something meaningful from it. Fortunately, there are enough powerful Python libraries to make this possible.

Tools like Hadoop make it even easier to handle big data. Hadoop is an open-source framework that allows data scientists to process huge amounts of data across numerous computers. It also allows data scientists to store massive amounts of unstructured data, such as videos, images, and text files, even if the data is not being used right away.

Companies like eBay, Facebook, and Twitter use Hadoop to optimize their search engines and to store copies of internal log files. LinkedIn uses it for their “People You May Know” feature. All of these companies process and analyze massive amounts of big data on a daily basis.

Nonetheless, it’s crucial to begin with the end in mind; companies must decide what they need from the data before they decide how much of it to analyze.

Sometimes, visualizing and modeling small data provides a company with all of the insights that it needs to make data-driven decisions, but the types of decisions and predictions that can be made with small data are limited and short-term.

The Growing Job Market for Data Scientists

A 2017 study by CareerCast highlighted the fact that data science was a relatively new career path at that time, but the job growth was predicted to be the highest of any other job in the United States. The study concluded that because the field was so new at the time, data science jobs were some of the hardest to fill. Nonetheless, they predicted massive job growth.

As we fast forward to 2019, it appears that this prediction has come true.

According to Indeed, data science is still a fast-growing field. On average, data scientists are making $120,000-$140,000 per year, with some earning over $200,000 annually. As of March 2019, there were over 90,000 vacancies for entry-level and mid-level data scientists on Indeed alone. There are no shortages of opportunities for aspiring data scientists.

Data scientists are working for health insurance companies, pharmaceutical companies, manufacturing companies across a wide variety of industries, credit card companies, start-ups, retail stores, tech giants, and so on. Every industry has a growing need for data scientists, which is what makes this such a versatile career option.

In Noble Desktop’s Data Science Certificate, we jump into hands-on data science practices right away. Students hit the ground running with Python fundamentals, including the analysis of real-world data sets using loops, functions, and objects.

As the course progresses, students will learn to work with tabular data (such as that found in CSV files or databases). They’ll learn to combine and aggregate data, using packages and libraries to create visualizations and to do advanced computing.

By the end of our Python for Data Science bootcamp, students will be able to extrapolate information from complex data sets, using it to make predictions and to make data-driven decisions using NumPy, Pandas, Matplotlib, and Sci-Kit Learn. From here, students will be able to explore a variety of other libraries and packages for Python. The possibilities are endless.

Continue reading

Learn Data Science for a New Career

  • Data Scientist source: indeed.com

    Salary in NYC

    $156,000 / year

    Data scientists collect, organize, and analyze large sets of data, providing analysis that is key to decision making. Governments, non-profits, and businesses of all types rely on data for forecasting, risk management, and resource allocation. Data scientists discover and analyze trends in data, and report their findings to stakeholders. They will use algorithms and models to simplify and mine data sets to create data-driven recommendations. Data scientists are needed across a handful of industries, especially the ubiquity of data and the reliance on it for business decision-making.

  • Data Engineer source: indeed.com

    Salary in NYC

    $133,000 / year

    Data Engineers create the infrastructure for data and format data into a useful system which Data Scientists use to analyze large amounts of data. Data Engineers can specialize in pipelines, databases or platforms, warehouses or infrastructure, or be generalists.

  • Machine Learning Engineer source: indeed.com

    Salary in NYC

    $188,000 / year

    Machine Learning Engineers create computer programs that enable machines to take actions without being specifically directed to perform those tasks. This job combines computer programming and data science to enable systems to learn and improve from experience automatically by using machine learning, a subset of artificial intelligence.

  • Data Analyst source: indeed.com

    Salary in NYC

    $77,000 / year

    Data analysts review large amounts of data to summarize, analyze, and visualize it and provide insights. Working from data from multiple, relevant sources, they create and maintain databases, and use statistical techniques to analyze the collected data. Data analysts must be able to communicate with others about what the data shows and to be able to provide realistic recommendations based on their analysis. Many industries such as healthcare, advertising, and retail rely on the work of data analysts to inform their business decisions and strategy.

Learn Where You’re Comfortable

Attend at our campus in NYC or learn remotely, live online

On Campus in NYC

185 Madison Ave, NYC

Get face-to-face interaction with an instructor and other students when you learn at our NYC campus. Courses are hands-on with a computer and software provided.

  • Live, interactive class
  • Experienced instructor in the room with you
  • Computer and software provided
  • Free retake within one year
Students seated in computer classroom with workbooks, paying attention to instructor

Live Online

Remote, from anywhere

Get the same interactivity and access to the instructor as in-person students. There are no extra fees and we’ll work with you to ensure your remote setup is perfect.

  • Live, interactive class
  • Experienced instructor teaching over Zoom
  • Remote setup assistance provided
  • Free retake within one year

Online Training Demo

1-Minute Overview

More about live online training

Data Science Resources

Free Resources

  • The 5 Stages of Your Data Science Journey with Python

    In this guide, we'll walk through the 5 phases of your data science journey with Python from the basics of Python to building machine learning algorithms.

  • Harmful Myths about Learning Data Science

    The internet is full of noise about what counts as “real” data science. This genre is generally a waste of time, but for beginners it can be particularly pernicious. If you’re already feeling like a fish out of water...

  • Free Online Class: Get Started in Data Science

    In simple terms, data science is exactly what it sounds like: the science of using data to obtain information, and, ideally, to make decisions based on the data that was obtained. In many industries, the goal of using data science is to make st...

  • Learning the Math used in Data Science: Introduction

    Data Science is truly comprised of two main topics: math and programming. However, one does not need to be a computer scientist or mathematician, one does not even need to have taken algebra or a basic programming class to start. 

  • Machine Learning Overview & Tutorial

    Learn what machine learning is, the various types of machine learning models, and walk through building a machine learning model in Python with this step-by-step guide. 

showing 5 of 5 resources

Upcoming Data Science Classes in NYC or Live Online

All times are listed in Eastern Time unless otherwise specified.

February 2023
Data Analytics Certificate
February 6–August 23
Weeknights 6–9pm
$4,995
156 Hours
NYC or Live Online

Learn the skills you’ll need to become a Data Analyst or Business Analyst, including data analysis, visualization, statistical analysis, and how to work with relational databases. Build a portfolio of projects and prepare for a career.

Add to cart
Python for Automation
February 15–22
Wednesdays 6–9pm
$425
6 Hours
NYC or Live Online

Learn Python to extract data from websites. Along the way, you’ll learn how to write loops so that your web scraping code can process a large number of pages.

Add to cart
Data Analytics Certificate
February 27–April 5
Weekdays 10–5pm
$4,995
156 Hours
NYC or Live Online

Learn the skills you’ll need to become a Data Analyst or Business Analyst, including data analysis, visualization, statistical analysis, and how to work with relational databases. Build a portfolio of projects and prepare for a career.

Add to cart
Python Machine Learning Bootcamp
February 27–March 29
Mondays & Wednesdays 6–9pm
$1,895
30 Hours
NYC or Live Online

Take a step beyond normal programming, into using algorithms that can independently learn patterns and make decisions. Machine learning skills are in high demand, as these algorithms now run the majority of trading on Wall Street and the product recommendations at big companies like Amazon, Spotify, and Netflix.

Add to cart
March 2023
SQL Bootcamp
March 6–8
Monday to Wednesday 10–5pm
$975
18 Hours
NYC or Live Online

Learn to extract info from databases by writing SQL queries, joining tables, aggregating data, and filtering results. You’ll learn PostgreSQL in this class, but the concepts apply equally to other databases such as SQL Server and MySQL

Add to cart
Data Science Certificate
March 6–April 5
Weekdays 10–5pm
$3,995
114 Hours
NYC or Live Online

Master the tools to become a data scientist: Python, SQL, automation, and machine learning. Learn Python programming fundamentals and analyze data with Pandas, NumPy, and Matplotlib, and query databases with SQL. Use machine learning to apply regressions and other statistical analysis to create predictive models.

Add to cart
Python for Data Science Bootcamp
March 11–April 8
Saturdays 10–5pm
$1,495
30 Hours
NYC or Live Online

Pick up Python fundamentals and quickly transition into analyzing real-world datasets. You will learn to how to clean and combine data, as well as generate useful statistics and visualizations. The final sessions will be focused on using linear regression to extrapolate from data and make predictions.

Add to cart
Data Science Certificate
March 11–August 5
Weekends 10–5pm
$3,995
114 Hours
NYC or Live Online

Master the tools to become a data scientist: Python, SQL, automation, and machine learning. Learn Python programming fundamentals and analyze data with Pandas, NumPy, and Matplotlib, and query databases with SQL. Use machine learning to apply regressions and other statistical analysis to create predictive models.

Add to cart
Python for Data Science Bootcamp
March 13–17
Monday to Friday 10–5pm
$1,495
30 Hours
NYC or Live Online

Pick up Python fundamentals and quickly transition into analyzing real-world datasets. You will learn to how to clean and combine data, as well as generate useful statistics and visualizations. The final sessions will be focused on using linear regression to extrapolate from data and make predictions.

Add to cart
Python Machine Learning Bootcamp
March 28–April 4
Tuesday to Monday 10–5pm
$1,895
30 Hours
NYC or Live Online

Take a step beyond normal programming, into using algorithms that can independently learn patterns and make decisions. Machine learning skills are in high demand, as these algorithms now run the majority of trading on Wall Street and the product recommendations at big companies like Amazon, Spotify, and Netflix.

Add to cart
Load 10 more courses

showing 10 of 32 courses

Yelp Facebook LinkedIn YouTube Twitter Instagram

Contact Us

Office Hours:
9am–6pm, Mon–Fri

(212) 226-4149 hello@nobledesktop.com

Location

In-Person in NYC

185 Madison Avenue 3rd Floor
New York, NY 10016

Campus Info

Live Online from Anywhere

Live Online Info

Noble Desktop is today’s primary center for learning and career development. Since 1990, our project-based classes and certificate programs have given professionals the tools to pursue creative careers in design, coding, and beyond. Noble Desktop is licensed by the New York State Education Department.

Adobe Certified Training Center

Win a Free Class!

Sign up to get tips, free giveaways, and more in our weekly newsletter.

© 1998–2023 Noble Desktop - Privacy & Terms

Compare selected courses Clear selection Comparison limit reached