How to Learn Python for Data Science

The number of options for learning Python for data science might be overwhelming at first glance. There are books, video tutorials, classes, and more to choose from; it all depends on your learning style and personal preferences.

Thanks to its rapid growth worldwide, data science is now a top field. Python literacy has become a requirement for many positions: if you want to learn data science, you’ll almost certainly have to master Python.

Here, we’ll discuss the various methods of learning Python for data science so you can determine how you’d like to get started.

What is Python for Data Science?

Python is among the most popular programming languages in the world, and many tech professionals learn it before moving on to other languages. According to leading publications, data science and machine learning pros consider Python their go-to programming language. Python is an essential skill for many development and data science roles, including:

• Data Scientist
• Data Engineer
• Software Engineer
• Data Analyst
• Python Developer

Artificial intelligence (AI) and machine learning (ML) are areas where Python for data science rules the roost. Building ML models and applying ML algorithms typically includes libraries like Scikit Learn or PyBrain. Data analysis requires Python libraries like Pandas and NumPy. And visualization with Matplotlib or Seaborn is popular in Python for data science. 

Read more about what Python is and why you should learn it for data science. 

What Can You Do with Python for Data Science?

Python is advantageous for data science professionals of all kinds. Its ease of use and scalability make it the top choice for Data Scientists, Data Engineers, and Data Analysts in virtually every sector of the economy.

Because Python is both easy to learn and powerful, its libraries and frameworks can be ideal for dealing with mathematical functions, data structures, and visualization. Here are some of the most common uses for Python in data science.

• Data Analysis - Python is easy to read and write, so it’s commonly used for complex data analysis—particularly handling large datasets. Top Python libraries for data analysis include:

• NumPy
• Pandas
• SciPy

• Data Visualization - Data science often requires visualization tools. Data professionals use charts, graphs, and even maps to present data in easy-to-digest ways. Top Python libraries for data visualization include:

• Matplotlib
• Plotly
• Seaborn

• Artificial Intelligence and Machine Learning - Machine learning, or ML, is a subset of artificial intelligence (AI). Data science pros use ML libraries like Scikit Learn for data classification and linear regression. Top Python libraries for AI and ML include:

• Scikit Learn
• PyBrain
• TensorFlow

In-Person Python for Data Science Training

Many Python for data science students find training in the traditional classroom setting the most effective way to learn. Advantages of this approach include:

• The expected level of engagement of in-person training
• Using course provider equipment
• Making valuable connections with peers and mentors

If in-person training has a drawback, it’s commuting and looking for parking. Overall, however, many students prefer in-person training.

Noble Desktop hosts a variety of Python for data science training options, like their Data Science Certificate, Python for Data Science Bootcamp, and Python Data Science & Machine Learning Bootcamp. Other options include their FinTech Bootcamp and Python Machine Learning Bootcamp.

You can find many Python for data science programs using the Classes Near Me search tool, like Python Advanced from AcademyX and Python for Automation from Practical Programming.

Live Online Python for Data Science Training

Although many students seek in-person Python for data science training, a growing number of students and busy professionals choose live online courses for their education. Virtual training via teleconferencing offers benefits similar to face-to-face coursework, but you can learn from the comfort of your home or office.

While you might find it convenient to avoid traveling to a classroom, your learning style might cause you to feel online learning holds a slightly lower level of engagement. Still, the ability to network with peers via instant messaging—and get 1-on-1 mentoring through teleconferencing— may provide a worthy substitute for in-person training.

You can find many live online Python for data science classes using Noble Desktop’s Classes Near Me search tool. Check out the following bootcamp-style programs:

• Python for Data Science Bootcamp - The Python for Data Science Bootcamp is open to beginners and covers everything from Python programming fundamentals to arrays, dataframes, and linear regression. Students can save by taking this course as part of Noble’s Data Science or Data Analytics Certificate programs.

• Python Machine Learning Bootcamp - A subset of artificial intelligence, machine learning (ML) is a primary focus for many data science professionals today. This bootcamp is also part of the Data Science Certificate, but you can take it separately if you’re already comfortable with Python libraries like NumPy and Pandas. Check listings for more detailed information.

• Python for Finance Bootcamp - Noble Desktop’s Python for Finance Bootcamp is ideal for anyone planning to become a Data Analyst, Financial Analyst, or Risk Manager. Get hands-on training from experts in this advanced bootcamp, or save by taking it as part of Noble’s FinTech Bootcamp.

Other alternatives include a Python for Data Science Immersive from Practical Programming, Coding Temple’s Python + Data Science, and BrainStation’s Machine Learning Certificate.

Free Online Courses & Tutorials

Those not yet ready to dive into a full-scale bootcamp or certificate program can still get an overview of Python for data science. Start learning Python for data science online for free. In this introductory course, you’ll learn fundamentals like:

• How to install Python using Anaconda
• Numeric data types
• Integers
• Pseudocodes
• Variable names
• Best practices

Additional free classes include Data Processing Using Python from Nanjing University, Data Science Math skills from Duke University, and the University of London’s Foundations of Data Science: K-Means Clustering in Python.

Read about more free Python and data science videos and online tutorials.

On-Demand Python for Data Science Classes

On-demand or self-paced options for Python for data science offer another approach to beginner-level training. These classes generally fall into the following types:

• Free
• Fee-based
• Subscription-based

Free classes are typically the shortest, ranging from one to four hours. Fee-based options run as high as $699 for Python certification exam prep programs, though others may cost as little as $85 for 25 hours of video instruction.

Subscription-based courses run a wider gamut. While you’ll have to pay to subscribe to a particular platform service, courses available to subscribers may include beginner, intermediate, and advanced Python training. Check listings carefully for pricing, course syllabi, and any prerequisite information before enrolling.

On-demand classes can offer substantial benefits, especially for students who need to learn after regular work hours or with unpredictable work schedules. Their biggest drawback is typically the lack of guidance or accountability. Most Python learners will move on to more formal training after starting with on-demand coursework. 

Current on-demand Python for data science classes include Noble Desktop’s Python Tutorial: Making a Twitter Bot in Python, 100 Days of Code: The Complete Python Pro Bootcamp from Udemy, and Data Visualization for Web Apps Using Python from Skillsoft.

Which Learning Method is Right for Me?

With so many different resources available to help beginners learn Python for data science, you might be unsure about which one is best for you. Everyone has different learning styles and preferences, and you can experiment with multiple tools to see which one feels right for you. One of the great things about directing your education is that you can decide which combination of tools you prefer; you don’t have to stick with what a teacher chooses.

If you are at the very beginning of your Python for data science journey, you might need to do some research first to determine what type of role you want to qualify for. Some courses include Python as part of a broader data science curriculum. Others cover Python programming at a general level, including Python for web development and other careers. The type of position you seek in the future may dictate how you want to begin.

It’s also essential to consider your current schedule before selecting a learning method. If you have a lot of responsibilities like a full-time job or family commitments, you may not be able to devote time to a structured course that requires you to attend at the same time every day. In this case, a self-paced class or video tutorials may be better since you can access them when your schedule allows. On the other hand, those with a more flexible schedule may prefer a structured course offered in-person or live online.

Why Learn Python for Data Science?

As Forbes noted in its Top Five Data Science Trends That Made An Impact In 2022, Python has emerged as “the go-to programming language for data science.” The article references multiple dominant data science libraries, including:

• NumPy
• Pandas
• Matplotlib
• Scikit Learn
• PyTorch

If you’re planning to study Python for data science, you can go into it knowing you’ll learn crucial skills and information. Top roles typically requiring Python for data science today include:

• Software Engineer
• Data Scientist
• Coding Engineer
• Software Developer
• Engineering Manager
• Data Analyst

Python for data science isn’t only for IT or software development, either. Sectors as diverse as banking/finance, manufacturing, agriculture, and media require Python data science expertise, and public sector roles like government and academia can require it, too.

Read more about why you should learn Python for data science.

Level of Difficulty, Prerequisites, & Cost 

You may think Python for data science will be challenging to learn, particularly if you have no coding experience. However, many students are surprised to learn that Python is the most popular programming language among data science professionals and one of the easiest to master. Python’s open-source license means an entire universe of libraries can be used free of charge, and its worldwide support community is always a mouse click away.

Before you start learning Python for data science, you should have a plan for how and where you’ll apply the knowledge you gain. Python programming fundamentals for a Data Analyst may differ from those of a Software Engineer. You should have basic computer skills, but you can use Python on Mac OS, Linux, or Windows.

You can download Python’s libraries and frameworks for free and find many online Python seminars and tutorials at no cost. However, you’ll eventually want to enroll in formal, paid training. If you learn Python as part of a broader data science curriculum, your approach will be different than if you want to focus on Python in a narrower sense.

Read more about how difficult it is to learn Python for data science.

Learn Python for Data Science with Hands-on Training at Noble Desktop

Because Python for data science involves two potentially different disciplines—Python programming and the broader data science field—not every student approaches it the same way. How and where you plan to use the knowledge you gain from Python for data science training may dictate your approach.

Noble Desktop offers multiple avenues to learn data science. Their Data Science Certificate includes Python programming fundamentals, machine learning, SQL to query databases, and plotting and dashboard libraries. This program prepares attendees for entry-level positions in data science and Python engineering.

Another option is Noble’s Python for Data Science Bootcamp. A hands-on 30-hour course, the bootcamp includes training in Numpy, Pandas, Matplotlib, and linear regression. Students can save by taking the Python for Data Science Bootcamp as part of the Data Science Certificate program as well.

If you prefer to peruse all the Python for data science training Noble Desktop offers, check out the Python Classes page. Here you’ll find bootcamps and certificate programs as well as shorter courses. Top certificate programs include:

• Data Science Certificate
• Software Engineering Certificate
• Data Analytics Certificate

Popular bootcamp options include:

• Python for Data Science Bootcamp
• Python Programming Bootcamp
• FinTech Bootcamp
• Cybersecurity Bootcamp

Other training options include:

• Python for Automation
• Cybersecurity with Python
• Python for Network Security

Noble Desktop’s bootcamps and certificate programs earn high marks from graduates. They are available live online or in-person in New York City. Additional perks include a verified Certificate of Completion and free retakes within a year after graduation. Many certificates and bootcamps also include 1-on-1 mentoring: check course descriptions for more information, including any prerequisites.

Key Insights

• If you want to learn data science, you will most likely need to master Python as part of your training.

• Methods for learning Python for data science include:

• Bootcamps and certificate programs, either live or in-person
• Video tutorials and seminars
• Articles, books, or blog posts
• On-demand or self-paced classes

• Top positions for Python for data science include:

• Data Scientist
• Data Engineer
• Software Engineer
• Data Analyst
• Engineering Manager
• Coding Engineer
• Python Developer

• Top Python libraries for data analysis include:

• NumPy
• Pandas
• SciPy

• Top Python libraries for data visualization include:

• Matplotlib
• Plotly
• Seaborn

• Top Python libraries for AI and ML include:

• Scikit Learn
• PyBrain
• TensorFlow

• In-person training has several advantages, including:

• Highest possible level of student engagement
• Availability of course provider equipment
• Valuable connections with peers and mentors

• Live online Python for data science training also has advantages, like learning from the comfort of your home or office.

• Free online courses are a great introduction to Python for data science and offer many benefits as well. Noble Desktop’s Intro to Python Fundamentals covers topics like:

• Installing Python with Anaconda
• Numeric data types
• Best practices

• There are also several types of on-demand or self-paced courses available online. The most common are:

• Fee-based programs
• Platform subscription-based classes
• Free courses

• You can get an immersive Python for data science education through an in-person or live online course with Noble Desktop. Among their most popular options are:

• Python for Data Science Bootcamp
• Data Science Certificate
• FinTech Bootcamp