Unlock the power of Python for data-driven decision-making as you master Python programming fundamentals and dive into data analysis. Acquire essential skills to clean and manipulate data, create insightful visualizations, and perform statistical analysis, all through hands-on projects with real-world datasets.
Learn Python, SQL, automation, and machine learning to become a Data Scientist. Gain Python programming, data analysis, SQL querying, and predictive modeling skills. Perfect for beginners, this program prepares you for entry-level data science and Python engineering roles. Unlock high-paying job opportunities in the field of data science.
Learn the skills needed to become a Python Developer, from Python programming fundamentals to web development with Django and Django REST. Develop in-demand skills with Django, a popular Python web framework used for back-end web programming, and build a portfolio of projects under the guidance of the lead instructor.
Learn the essential skills needed to become a Data Analyst or Business Analyst, including data analysis, data visualization, and statistical analysis. Gain practical experience through real-world projects and prepare for a successful career in the field of data analytics.
Learn the fundamentals of machine learning, including regression analysis and classification algorithms, in this practical, hands-on course. Gain the skills needed to solve real-world problems using machine learning, with a focus on Python programming and data science libraries.
Learn Python programming from scratch. Master variables, data types, loops, and functions, and tackle real-world challenges with object-oriented programming. Create a GitHub portfolio to impress employers and master practical Python skills.
Learn how to use Python to extract data from websites and write loops for processing a large number of pages. This course covers topics such as HTML and CSS, Python fundamentals, web scraping exercises, storage and scheduling, and real-life examples of scraping valuable data.
Learn to gather, manipulate, and analyze real-life data in this course, where you'll gain hands-on experience with Python's NumPy and Pandas libraries. Develop your data visualization skills using Matplotlib, Seaborn, Plotly, and Dash Enterprise, and complete real-life projects that can be deployed online.
Create, style, and enhance web apps with AI capabilities. In this advanced Python course, you'll develop a powerful sentiment analysis web application with Flask and the OpenAI API integration and learn how to take your coding projects to the next level with AI.
Python is a high-level programming language with many different uses, including developing websites and software, system scripting, task automation, and analyzing and visualizing data. It is considered to be relatively easy to use and extremely versatile. Additionally, Python has a supportive community with experts to help new people learn. It has been around for a while, so the community is quite large. Python’s libraries and frameworks also make it one of the easiest languages to use. Anyone can access Python for free since it’s open source. It also has a multitude of cross-platform uses, making it applicable in many different situations.
The TIOBE Index, which tracks the popularity of programming languages, ranks Python as the most popular programming language in the world. In a recent GitHub blog post, the author notes, “Python is everywhere—and it’s been used to build a significant number of the technologies, websites, and even systems most people encounter on a daily basis. It powers everything from your favorite video streaming service to the ML algorithms that can help you make your next cryptocurrency trade.”
Python was created by a programmer named Guido van Rossum and was first released in 1991. Its name comes from a BBC television show called Monty Python’s Flying Circus, which aired in the 1960s and 1970s. The Python Institute, a nonprofit group that aims to promote this language, notes that it is unusual for a coding language to be created by a single person, but says that this was the case with Python. It states, “One of the amazing features of Python is the fact that it is actually one person’s work. Usually, new programming languages are developed and published by large companies employing lots of professionals, and due to copyright rules, it is hard to name any of the people involved in the project. Python is an exception.” While van Rossum created Python, the evolution and development of this language also owes a lot to the contributions of its thousands of users. The Python Institute explains, “The speed with which Python has spread around the world is a result of the continuous work of thousands (very often anonymous) programmers, testers, users (many of them aren’t IT specialists) and enthusiasts.”
Python is a great language to learn for beginners, and it works well with other languages like Ruby and C. Python has even blended with other languages, creating CPython (combining C and Python) and RubyPython (a combination of Ruby and Python). Learning it will prepare you for many different jobs in data science, AI, machine learning, and web development, to name a few. Overall, Python is a great first language for someone looking to get into coding.
Python is a popular tool for developing web pages and applications. Back End Developers use it to work on the back-end of websites. The back-end is the part of the site that is critical to its functioning but is not seen by users, and it includes things like APIs and servers. Software Engineers—who design, create, and maintain software—also use Python. This language has a large community, and there is a lot of reusable code and frameworks available to developers.
Python is also a popular tool for data science, machine learning, and financial analysis. It is used in jobs such as Data Scientist, Data Analyst, Machine Learning Engineer, and Financial Analyst. A GitHub blog post discusses why Python is so popular in these fields, explaining, “Since its syntax is easily understandable and adaptable, people with little-to-no development experience can easily learn Python and use it to manipulate data for research, reporting, predictive or regression analyses, and more.”
Another popular use of Python is data automation. The GitHub blog post states, “With Python, you can learn how to automate just about anything by using either built-in modules or pre-written code from its robust library. Or you can write your own custom scripts to perform specific actions…. Python also has a robust set of testing frameworks, which makes it an excellent language for test automation.” Python for automation helps save time and also prevents errors.
Python classes vary by school, so what you learn will vary; however, most courses cover the same fundamental Python skills, which include the Python language, libraries and frameworks, data structures and algorithms, and best practices.
When you take a Python class, you’ll learn to use the Python language, which has its own unique form and rules. For example, you’ll learn Python syntax, which means the way words and phrases are arranged in this language. Some other language-related Python topics include conditionals, variable expressions, functions, data types, and loops. You’ll also learn how to find errors in your Python code and how to fix them.
Libraries and frameworks are valuable, time-saving tools for programmers working with Python. A library is a collection of prewritten code that can be used for a wide range of different tasks, and a framework is a collection of prewritten code that can be used to create a complete application. Python has its own libraries and frameworks, which save programmers from writing everything from scratch. Popular Python libraries include Pandas, Matplotlib, and NumPy. Popular frameworks are Pyramid, Flask, and Django.
A data structure is something that is used to store and organize data in a specific way. An algorithm is a procedure that can be used to solve a specific type of problem. Both algorithms and data structures are an important part of learning Python and will be covered in most courses.
Best practices are also covered in most Python classes. These are practices intended to ensure that the code you create is readable, high-quality, and consistent. Python best practices include writing in the simplest way possible, keeping your code organized, and testing it regularly.
Learning Python is a much-needed skill in the Los Angeles area. The area is rapidly becoming an alternative to Silicon Valley for startups, so learning Python can help you find careers in a quickly growing field. Notable companies such as Nordstrom, MotorTrend, and Ranker were developed with Python in Los Angeles. The Economic & Workforce Development Department comments on the size and diversity of the Los Angeles economy, stating, “Los Angeles is a global economic powerhouse, boasting the world’s third-largest metropolitan economy. For generations, people from around the globe have come to Los Angeles to create the future and in turn, helped build one of the most diverse and dynamic cities in history.” According to the Los Angeles County Economic Development Corporation, leading industries in this city include aerospace, biosciences, entertainment, EV and advanced transportation, design, and IT.
Los Angeles is known as a major tech hub. According to a recent report by CBRE, it is a top tech market. The organization published an annual Scoring Tech Talent report, and in 2023, it placed Los Angeles at the number fourteen spot on its list. CBRE reports that the area added 36,650 tech jobs between 2017 and 2022. In addition, it says, “The average tech talent wage in the region has increased by 20% between 2017 and 2022, with tech workers earning $112,905 on average.” CBRE explains that tech growth in Los Angeles is the result of several different factors, including a large number of tech graduates being produced in the area, the existence of a desirable lifestyle, and the availability of many tech job opportunities.
Los Angeles is also home to many large financial companies, meaning that there are numerous job options for Data Analysts who want to work in finance. This city is a top location for FinTech. In 2023, it moved up to the number six position on the Global Financial Centres Index, which is a list of the world’s top financial centers created by Z/Yen Partners and the China Development Institute.
Many Python-related jobs don’t require you to be certified; however, that doesn’t mean that it isn’t a good idea to get certified. According to a statement by the Institute for Credentialing Excellence, a professional organization that develops standards for certification and certificate programs, there can be numerous job-related benefits to certification. It says,
Certification holders benefit from:
Many employers report that they are more likely to consider job candidates who are certified because a certification proves that candidates possess a certain level of knowledge, and also shows that they are committed to personal development.
Two different career paths are available for Python experts, and both can be lucrative. One option is to use Python for development, creating software, or developing the front and back-end of websites. Job titles related to development include Software Engineer, Full Stack Developer, and Back End Developer. According to Payscale, a Software Engineer in Los Angeles earns about $105,000 yearly, and a Full Stack Developer earns almost $100,000. Glassdoor reports that the average salary for a Los Angeles Back End Developer is $102,000. The Bureau of Labor Statistics (BLS) is a federal agency that tracks job statistics and publishes projections about jobs in the United States. It reports that about 53,000 Software Developers are employed in the Los Angeles metropolitan area, and almost 3,000 Web Developers.
Another option is to use Python in a data-driven career. Some of these career options include data engineering, data science, and data analysis. All of these careers involve taking large amounts of data, processing it, and packaging it in a way that can help an organization thrive. Some of the data-driven jobs you might find are Data Scientist, Data Analyst, Data Engineer, and Machine Learning Engineer. A Los Angeles Data Scientist earns $107,000, according to Payscale, and a Data Analyst $70,000. For a Data Engineer, the average salary is $104,000, and for a Machine Learning Engineer, it is $117,000. According to the BLS, Los Angeles has the third-highest employment of Data Scientists among U.S. metropolitan areas, with more than 7,000 people employed in this profession.
Rapid job growth is predicted for several jobs where Python is used, making this likely to be a good career investment. The BLS finds that over the next ten years, there will be above-average job growth for Data Scientists, Computer and Information Research Scientists, Software Developers, and Web Developers, all of which involve the use of Python. Growth is predicted to be 35 percent for Data Scientists, 23 percent for Computer and Information Research Scientists, 25 percent for Software Developers, and 16 percent for Web Developers and Digital Designers.
Another good reason to learn Python is that it is an extremely versatile language, with a wide range of different uses. The Python Institute says, “Programming skills prepare you for careers in almost any industry, and are required if you want to continue to more advanced and higher-paying software development and engineering roles. Python is the programming language that opens more doors than any other. With a solid knowledge of Python, you can work in a multitude of jobs and a multitude of industries. And the more you understand Python, the more you can do in the 21st Century.” In fact, the organization argues that Python has so many uses and has become such an integral part of life that it can be useful to know even if you don’t plan to use it for work.
You can start learning some basic Python skills in a matter of hours or days, but most people say that it takes several months to learn this language. Really mastering it can take even longer. If you already have experience in programming, you may learn more quickly. Taking a paid Python course is a great way to speed up the learning process because you’ll be able to learn under the guidance of an experienced instructor. In a recent LinkedIn article, the author maintains that consistent practice is also a vital part of learning. She says, “Consistency is the key to mastering Python effectively. Treat coding as a daily practice, even if you can only spare a few minutes each day. Consistent practice helps reinforce concepts and build muscle memory for writing code.” She suggests utilizing online quizzes and exercises and breaking down learning into smaller units so that it feels more manageable and engaging.
Many people say that Python is one of the easiest programming languages to learn. For instance, the Python Institute insists, “It is easy to learn–the time needed to learn Python is shorter than for many other languages; this means that it’s possible to start the actual programming faster.” Python has a relatively simple and readable syntax that many people find intuitive. Another reason that many people find Python relatively easy to learn is that this language has a large community, with many different learning resources for beginners to draw on. In a recent LinkedIn article, the author explains that it also has an extensive library for new programmers to use, which simplifies the learning process. He states, “Python boasts a vast standard library that covers a wide range of functions and modules for various tasks. This extensive library reduces the need for developers to reinvent the wheel. Beginners can tap into this rich resource to accomplish tasks without having to write complex code from scratch. Whether you need to work with files, handle regular expressions, or perform network operations, Python’s standard library likely has a module that simplifies the task.”
Learning Python alone may not be enough to get you a job. It can also be a good idea to expand your resume by learning some complementary skills. These will vary depending on how you plan to use Python, but may include things like other coding languages, development tools, frameworks, and data analysis skills. In addition, soft skills can be an asset in any career.
Python is one of the most popular coding languages; however, it is far from the only one. There are hundreds of different languages. The specific languages that will be useful to you will depend on how you plan to utilize Python. If you’re going into development, you may want to learn HTML, CSS, and JavaScript, which are fundamental programming languages. If you want to work in data analysis, languages like SQL and R may be useful, since these are very popular in this field.
Back-end tools are tools that developers use for working on the back-end of a site. They help developers accomplish a variety of tasks, like communicating with the front-end of the site or managing the storage of data. An example of a back-end tool is MongoDB, which is a free open-source database that is often used by developers.
Frameworks are another popular developer tool. These are pre-existing structures that you can build on, and they help speed up the development process. They are created around a specific language. Ruby on Rails is a popular framework.
If you’re planning to focus on data analysis rather than development, you will likely need to learn a range of data analysis skills. For example, Data Analysts typically need a good understanding of statistics, which is a branch of mathematics involved with collecting, analyzing, and interpreting data.
Soft skills are likely to be beneficial in any career. They include teamwork, communication, and adaptability, and can help you maintain good relationships and work well with other people. Indeed stresses, “These skills are equally important as technical abilities such as writing code and creating user interfaces. Soft skills complement technical skills by allowing one to identify the needs of team members and organise ideas for developing programmes.”
When you research Python classes, you’ll find that there is more than one type of class format. Students can choose to learn either in-person or online, and each format has its own distinct benefits and downsides. In-person learning is the traditional way to learn a new skill; students learn in a physical classroom space, with other students and a live instructor. Many students still prefer this format because they find in-person instruction to be the most engaging and effective way to learn something new. With the in-person format, it can also be easier for the instructor to tailor instruction to those students who are in the class and to see whether students need additional help. Another thing that many people like about in-person learning is that, because they are in an environment with minimal outside distractions, it can be easier to focus on what they are learning. One of the biggest downsides to in-person learning is that students have to be physically present, which limits their training options to those they can commute to.
Live online classes, on the other hand, offer a lot more flexibility because students do not have to physically commute to a classroom. Instead, students attend by logging in online and attending a live meeting through their computer screen. They still get live instruction and interaction and are able to ask questions and get immediate feedback whenever they need to, but they can attend from home, the office, or any other location of their choice. Because they don’t need to be physically present, students who learn live online have more class options, including classes based in other cities and states. This can also mean that students may be exposed to a more diverse group of students. Another reason that many students like live online learning is that they find it less intimidating to learn via computer rather than in a room full of strangers. Downsides to this format include the fact that students typically have to provide their own equipment and software, and that they may encounter technical problems.
Another way to learn is by taking an on-demand class. With this format, you also have the flexibility of attending from any location that you choose; however, you don’t have to log in at a specific time for a live lecture. Instead, on-demand classes take place asynchronously, which means that you progress through the material at your own pace. You can pause, rewind, or even fast-forward whenever you need to. This option is popular with students who have a busy schedule and are looking for maximum flexibility. On-demand learning is often cheaper than live options since there is no classroom facility and no live instruction. It can require more motivation and focus than live classes, so if you’re not good at working independently, on-demand learning may not be the best choice for you.
Noble Desktop offers live online Python classes for data science and web development that are fit for beginner, intermediate, and advanced Python programmers. The Python Developer Certificate is a popular Noble option. This program provides both foundational and advanced skills essential for a rewarding career in Python development. The early course sessions explore the basics of Python, covering elements like syntax, dictionaries, custom functions, and complex sorting algorithms. As the course advances, attendees will learn about object-oriented programming principles, API integration, and web database management using SQL. Much of the curriculum is devoted to working with Django, an important Python framework for back-end development, and Django REST, a specialized framework for building web APIs. The program culminates in students creating a portfolio that showcases skills in high demand in the development field. In addition to the regular course material, students have the opportunity for four individual mentoring sessions, where industry professionals provide portfolio reviews and share crucial insights into navigating the job market. This is a three-week class.
Noble also offers a Data Science Certificate for those interested in leveraging the capabilities of Python in the field of data science. This program is a thorough introduction for individuals pursuing a career in data science and Python engineering. Taught by experienced industry experts, participants gain the skills needed to analyze data effectively, create machine learning models, and produce interactive data visualizations using Python and SQL. The course goes in-depth into key Python libraries specialized for data analysis and task automation. Additionally, attendees build machine learning models to solve real-world challenges and implement improvements. Using advanced graphing and dashboard libraries like Matplotlib and Plotly, students create dynamic dashboards and data visualizations, thereby contributing meaningful projects to their portfolios. Beyond the core instructional hours, the program also includes six specialized mentoring sessions. During these times, industry experts provide invaluable portfolio reviews, assistance with complex course topics, and strategic advice for career growth. This is a four-week class.
Another online option is Python Machine Learning Immersive, which runs through Practical Programming. Machine learning algorithms are increasingly central to the operations of leading companies, influencing everything from financial trading strategies to product recommendations on platforms such as Amazon and Netflix. This course introduces participants to the detailed functionalities of Python’s scikit-learn library, enabling the development of robust machine learning algorithms like logistic regression and random forest. The curriculum thoroughly addresses data division into training, testing, and cross-validation sets and delves into key theoretical concepts like overfitting, variance, and bias. Moreover, students learn how to accurately evaluate the effectiveness of their models and gain insights into selecting the most appropriate algorithms for their specific goals. Upon successful completion, participants receive a digital certificate, which can be easily displayed on professional platforms such as LinkedIn. Students who want to take this class should have a foundational understanding of Python as well as its essential data science libraries, namely Pandas and NumPy. For those who may need to acquire this preliminary knowledge, an enrollment option exists for the Python for Data Science Bootcamp, serving as an excellent foundation for this immersive course.
Python courses aren’t limited to upskillers or people looking for an alternative to college. For students looking to get a head start in the tech field, NextGen Bootcamp offers summer and after-school Python classes for high schoolers, which are a great way to begin Python. Classes like this can boost your résumé for college, help you land your first summer internship, or just give you early experience for a career. Python Data Science & Machine Learning Live Online is a 45-hour course. The curriculum introduces students to Python programming, and they acquire hands-on experience in reading and writing code while also interacting with real-world databases and case studies. As students become proficient in database management and queries using Python, the course then segues into the fundamentals of machine learning. Here, students gain insights into the architecture and inner workings of machine learning algorithms, empowering them to develop basic algorithms and execute simple machine learning tasks. This program offers a robust introduction to both data science and computer science, making it a fitting choice for beginners interested in coding and keeping pace with evolving technologies.
Another option for learning Python is through your company. Python is very useful in many different industries, and companies are often willing to cover the training. There are many different options for corporate Python training from Noble Desktop. Noble’s training options are highly flexible, with onsite or live online courses available. If your organization is interested in building more useful skills, consider a custom program through Noble Desktop. Programs can be tailored to your needs, from beginner to advanced, and customized to cover specific topics like finance, development, data science, or data analysis. Another corporate training option is to purchase vouchers for Noble’s regular group classes and let employees pick their own training schedule. There is a discount for the purchase of multiple vouchers. For more information about corporate training, speak with an instructional consultant by contacting Noble Desktop today.
Those seeking a chance to sharpen their skills in tech, design, business, or data can look no further than the opportunities in Los Angeles. The city is more than just Hollywood; it’s a collection of professional services and companies that stretch from the innovative companies in Silicon Beach to the more corporate areas of downtown L.A. Python is one of the most versatile programming languages to learn if you want to work across industries. It's used for everything from web development and automation to data analytics and more. It's a highly valuable skill that opens doors in tech, data science, and software development. For those interested, Noble Desktop’s partner school, VDCI, offers classes taught by industry experts who are passionate, willing, and ready to impart their knowledge to students and professionals alike. They offer insight based on their real-world experience, which makes all the difference when learning a new skill from scratch or while looking to advance in your field.
Los Angeles-based learners can take advantage of the training at 3904 Groton Street, San Diego, California, located directly in the Point Loma neighborhood. Driving from Los Angeles, you’ll take I-5 South all the way. Those who prefer public transportation can hop on the Amtrak and commuter rail services connecting to San Diego from L.A., making it a quick way to access the campus. The facility is designed for interaction, offering students access to top-rated instructors and modern workstations.
With over 20 years of experience, Dr. Deanne Larson has built a reputation as a pioneer in the Los Angeles data science and analytics world. As the founder of Larson & Associates LLC, she has partnered with Fortune 500 companies and FinTech firms to help shape AI strategies and implement solutions through machine learning. She’s worked with global enterprises, particularly in designing their data systems. Her accomplishments go beyond the norm, however, as she’s also been part of projects that serve 225 million customers worldwide and others that require developing cutting-edge data governance frameworks for cloud and blockchain technologies. She’s a seasoned instructor as well, having taught at City University of Seattle, where she mentored doctoral candidates and designed data analytics programs. She holds several doctoral degrees that, paired with her extensive experience, position her to teach subjects like AI, Python, data, machine learning, and project management.
Michael Wilson is a Licensed Architect in the State of California and an Autodesk Certified Platinum Revit Instructor, one of only 20 professionals worldwide to hold this title. With over 25 years of experience in architecture, Michael has contributed to award-winning commercial and municipal projects, including facilities for pharmaceutical companies and landmarks such as the El Cajon Animal Shelter and the Mission Hills Library. Michael teaches and develops Revit courses that emphasize real-world application through project-based learning. Over the past decade, he has trained thousands of students in the Los Angeles AEC community, helping them master workflows. Michael is also an Autodesk Certified AutoCAD and Revit Professional, specializing in Revit certification and interior design software.
John O’Malley is a Registered Architect with more than a decade of experience leading Los Angeles teams through all stages of design and construction. His professional background spans different sectors, where he has earned recognition for his technical precision and leadership. A licensed architect in California, John also holds LEED AP BD+C certification and is an Autodesk Certified Instructor (ACI Silver). Most recently, he teaches AutoCAD courses that prepare students to apply drafting and design principles in real-world settings. John is passionate about mentoring the next generation of design professionals, contributing to the ACE Mentor Program.