How to Learn Python for Data Science Online

If you’re starting with learning a new skill, you can find dozens of tips and resources online; learning Python for data science is no different. Python is a beginner-friendly programming language with a massive number of applications. Numerous companies, from Google to Spotify, use Python for everything from data analysis to development.

If you’ve always wanted to learn Python for data science, there are plenty of options at your fingertips. From free tutorials to live classes, the following article outlines your options so you can decide how to learn using the best method for you.

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

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.

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.

Free Intro 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.

Comparing Online Methods with In-Person Learning 

The bootcamp or certificate training model can be the perfect way to learn Python for data science. In-person programs remain the format of choice for many students, especially those who prefer the traditional classroom experience.

This section will cover the three main training formats:

• In-person courses
• Live online (via teleconferencing) programs
• On-demand or self-paced classes

Many students and busy professionals consider live online and in-person classes the most engaging, interactive methods of learning. Students can ask questions and receive immediate feedback, get guidance building portfolios, and interact with like-minded peers.

Face-to-face training also offers additional advantages, like networking opportunities and computer labs with up-to-date software.

Many students appreciate the benefits of virtual live bootcamps or certificate programs to master Python for data science fundamentals. Live online training offers a learning experience comparable to in-person training, with expert instructors who have experience in the field. You can get immediate feedback as you would in an in-person class, but from the comfort of your home or office. Instructors can even control your screen, with permission. If there’s any drawback to online classes, it’s that you have to use equipment you own, which means tech support is up to you.

On-demand or self-paced training is typically the most affordable option and can be a great way to start learning Python for data science fundamentals. However, this method doesn’t offer the benefits of live instruction and has the potential to be outdated. On-demand courses vary in length and price, from free one-hour video seminars to programs that cost more than $500. Although you may consider a self-paced course at that price a bargain, most students find that lack of engagement or accountability for assignments makes them want to pay for live training rather than prerecorded videos. Self-paced training typically works best as an introduction rather than a primary curriculum.

Tips to Succeed when Learning Python for Data Science Online

Learning Python for data science online can be challenging, no matter what program you choose. Scheduling for success, taking advantage of your network, and focusing on self-care are all essential elements virtual training—especially for students and busy professionals.

To get the most from your online education, consider how to best implement these suggestions. In-person training may emphasize accountability, but if you’re learning from home, you may feel at times like you’re on your own. Fortunately, you can always get help from fellow students or instructors, online forums, and the notes you take during sessions.

• Schedule for success - One of the most important aspects of any Python for data science course is what you do outside the classroom. Scheduling for success means you never miss a session, and you set times for completing assignments and studying materials. Those who enroll in full-time programs will have much less flexibility in their schedules than those who take a course part-time over several months. If you have work or family obligations that take up much of your time, a part-time class may be your only option. In either case, consider using a calendar tool like Google Calendar or iCal to block out times for study periods, deadlines for assignments, or meetings with instructors or fellow students.

• Take advantage of your network - If you enroll in a bootcamp or certificate program, you can expect to learn from expert instructors with experience in the field. While your instructor most likely has more expertise than anyone else in your class, that doesn’t necessarily mean all your fellow students are beginners. Many Python for data science bootcamp participants already work in data-centered roles and take these courses to level up from their current position. Thanks to collaboration apps like Slack or Microsoft Teams, you can often network with fellow attendees. During off hours, you may also be able to get information from programming professionals, since Python has a massive support community all over the world.

• Focus on self-care - Anyone taking a Python for data science course in addition to school or work can easily forget: it’s a significant addition to the schedule. Focusing on self-care can mean acknowledging the extra energy required and taking steps to manage the challenge. Self-care includes more than exercise or proper nutrition; it also means:

• Getting sufficient sleep
• Balancing family and work obligations
• Taking time for leisure activities

Of these, getting enough sleep may be the most underrated. While corporate CEOs may brag about sleeping four hours per night, studies show that even the notion of “making up” lost sleep on the weekend is a fallacy. Around one-third of U.S. adults do not get enough sleep. Seven to eight hours per night should be the minimum on average, and less than six hours of sleep can cause significant health problems.

With these tips in mind, you can plan for success in Python for data science. Take care of essentials, and make the most of the opportunities, especially if you’re taking an immersive bootcamp or certificate program.

Key Insights

• If you’ve always wanted to learn Python for data science online, there are plenty of options at your fingertips.

• Python is an essential skill for many data science roles, including:
  • Data Scientist
  • Data Engineer
  • Software Engineer
  • Data Analyst
• 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
• Live online Python for data science training has several advantages, notably the ability to learn from the comfort of your home or office.

• Many students appreciate the benefits of virtual live bootcamps or certificate programs to master Python for data science fundamentals. Additional benefits include:
  • Expert instructors with experience in the field
  • Immediate feedback comparable to in-person training
    
    
• Free online courses are also a great introduction to Python for data science and offer many benefits as well. Noble Desktop’s Intro to Python Fundamentals tutorial covers topics like:
  • Installing Python with Anaconda
  • Numeric data types
  • Best practices
• Tips for online learning success include:
  • Scheduling time for studying materials and completing assignments
  • Networking with peers and instructors
  • Focusing on self-care, including balancing work and family, making time for leisure activities, and getting enough rest

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.