Build your Python programming confidence through projects that explore automation, data, and web development. Learn how coding can streamline processes and inspire innovation.
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 free, open-source, object-oriented programming language developed in 1991 by Guido van Rossum. It is easy to learn and read because of its simple yet powerful syntax. Python has an array of uses from developing software and websites, to automating tasks, analyzing, and visualizing data.
Python is often used in web development to create the back-end of an app or website. Because of its modular nature, Python is especially helpful for scripting, or creating code that can be used to automate tasks that must be executed repeatedly. Python has several powerful libraries for data science and analytics. These free libraries are considered to be some of the most robust available for coding.
People who want to change careers to become a Web Developer or Data Scientist often learn Python first before other coding languages. Python is used in many different applications such as web development, data analysis, artificial intelligence, and machine learning, so many people choose to learn it first.
Web Developers, Software Engineers, Full Stack Engineers, DevOps Engineers, Python Developers, and Data Analysts use Python and its libraries for many daily tasks. The Beautiful Soup library is a powerful tool for scraping and mining data from APIs and the internet. NumPy and Pandas are used for data processing and modeling, and Matplotlib creates data visualizations. People with Python skills use it to analyze different types of complex datasets and structures.
When you sign up for a Python class, you will learn foundational programming concepts, like loops, functions, and objects, and how to handle different types of data. The course will also cover how to use conditional statements and object-oriented programming. You will also learn about the many useful Python libraries, like NumPy, Pandas, Matplotlib, and scikit-learn.
In a Python class, you will learn data basics. Types of data include statements and expressions, variables, integers and floats, and strings. Some data structures covered in a class include functions and methods, lists, indexing and slicing, and Booleans.
A course will teach you how to structure programs. This includes complex data structures and control flow topics like dictionaries, conditional statements, for loops, and creating functions.
You will also learn about packages and object-oriented programming, including classes and objects, modules and imports, and packages and documentation.
A Python course will also cover arrays, a linear data structure with sequentially arranged elements. NumPy, or Numerical Python, is a Python library coders use to work with arrays. Pandas stands for Python Data Analysis Library and is for working with datasets. Pandas can analyze, clean, explore, and manipulate data.
Two other skills covered in a Python programming class are data analysis and data visualization. Courses teach you how to filter and clean data, group by operations, and create pivot tables. Once you have analyzed the data, you will learn to create visualizations like bar charts, scatter plots, and histograms using Matplotlib to identify and highlight trends and patterns.
Python is considered one of the best starter languages for novice programmers. The straightforward syntax and versatility of Python make it a top choice for people who are learning to code. However, that doesn't mean that it isn't challenging. If you have prior experience with coding, you will have an easier time learning Python. Some of the biggest challenges to learning Python include grasping the concept of object-oriented programming, knowing what Python is used for, and recognizing problems that need to be solved. A class can help you overcome these challenges.
As with difficulty, the length of time it takes to learn Python depends on prior experience and amount of time you can spend practicing. Most students become proficient in two to six months. It also depends on what you plan to do with your Python training. If you are learning Python to switch to a career as a Data Scientist, you may go for a deeper level of training than if you want to use Python for website development.
What to learn alongside Python depends on what you plan to do with the language after training. If you are interested in web development, you will want to learn other coding languages like HTML, CSS, JavaScript, Java, or the C languages. If you plan to change to a career in data science, learning about some of the other Python libraries, like TensorFlow and SciPy, is a good choice, as is exploring data visualization tools like Tableau and Power BI. Signing up for a certificate program in data science can give you the skills to work with artificial intelligence or machine learning.
Any industry that performs data analysis can use people with Python skills, but the web development, data analysis, machine learning, and finance industries use Python the most.
The web development industry builds websites and mobile applications for clients. Some web development companies in San Francisco include Innowise, Yellow, Bloorsoft, Three29, and Moonstone Interactive.
The data analysis industry uses many coding languages, including Python, to work with large datasets for making business decisions. These are some of the top data analysis firms in San Francisco: DISQO, Asana, Doximity, Tempus AI, West Monroe, Ascend.io, VidMob, ZS, Hex, and John Deere.
Python is used for machine learning and artificial intelligence applications to allow computers to make decisions or predictions that they have not been specifically programmed to make. Some Bay Area machine learning firms include Forge, TrueML, Snap, Tempus AI, Grammarly, PagerDuty, Cruise, NextRoll, Liftoff, and Redflag AI.
The finance industry was one of the first to embrace technology like Python object-oriented programming. Some of the finance companies in San Francisco using Python include Square, Toast, Human Interest, CAIS, SoFi, Navan, Upgrade, and Cedar.
Tech careers in general are well paid and in great demand, especially coding careers. Some job titles for people with Python skills include Web Developer, Full Stack Developer, Software Engineer, Machine Learning Engineer, and Cybersecurity Analyst.
Web Developers use programming languages like Python to create websites and mobile applications. They integrate graphics, audio, and videos into products and build and test prototypes. The U.S. Bureau of Labor Statistics reports an expected job growth rate of 16% for this field over the next ten years and a median annual salary of $92,000. Web Developers in San Francisco earn about $108,000 a year.
Software Engineers also work with programming languages. Instead of creating website apps, Software Engineers develop many types of products from operating systems to gaming applications. In California, the yearly salary for Software Engineers is $150,000.
Full Stack Developers go beyond website development and work on the entire software stack, including both front-end and back-end operations. Full Stack Developers in San Francisco make around $150,000 annually.
Data Scientists use Python and other programming languages to collect, clean, analyze, and visualize data. They also write algorithms and create machine learning models. Data Scientists in the U.S. earn a yearly salary of $108,000 and $158,000 in San Francisco.
Cybersecurity Analysts implement and monitor security protocols for companies and government agencies. They check for vulnerabilities in systems, educate network users, and recommend security enhancements. The median yearly salary for a Cybersecurity Analyst in the U.S. is $120,000 and $171,000 in San Francisco.
General Assembly offers an in-person Python Programming Short Course in San Francisco. The class covers fundamentals for Python and object-oriented programming for web development and other applications.
Getting Started with Python is another in-person option from AcademyX. This introductory class covers interactive vs. batch execution, Python IDLE, and instruction on data types, Python expressions, and operators.
Learnit has a Python Fundamentals course for students with no prior programming experience who are looking to learn the basic skills needed for Python programming. The course will cover foundational Python concepts, including data types, control statements, using functions and modules, handling exceptions and debugging programs, working with lists, and how to work with a variety of data types.
Intro to Python Coding for Machine Learning from iD Tech presents the essentials of machine learning using Python. Students will learn to work with object-oriented programming and neural networks.
Students who want to work in the financial services industry can sign up for Berkeley Boot Camps' FinTech Bootcamp. The course covers FinTech topics and how Python is used in blockchain, advanced trading algorithms, and cryptocurrency.
If you are looking for a live online course, Noble Desktop offers several Python bootcamp and certificate courses. Noble’s Python for Data Science Bootcamp is open to beginners who want to build programming and data analysis skills using Python. The course will get you up and running with Python programming and data science to generate insights from data. Learn data analysis, data visualization, and statistical analysis. Noble’s Python Developer Certificate is another beginner-friendly option to learn Python for software development. The course covers Django and Django REST in addition to other developer tools such as Git and SQL. If you are interested in more advanced Python skills, try Noble’s Python Machine Learning Bootcamp. Expand your Python programming skills into machine learning and algorithms that can independently learn patterns and make decisions. The course begins with linear and logistic regressions, the most time-tested and reliable tools for approaching a machine learning problem. Students then progress to algorithms with a different theoretical basis such as k-nearest neighbors, decision trees, and random forest. You will learn how to measure the accuracy of your models, as well as tips for choosing effective features and algorithms, plus important statistical concepts such as bias, variance, and overfitting. In Python for Automation, you will learn to automate tasks using Python for various applications. This course is meant for those with prior Python experience looking to learn automation techniques like scheduling programs, updating spreadsheets, and web scraping. Topics include HTML and CSS basics, web scraping techniques, working with spreadsheets using Python, and scheduling scripts. This course offers flexible scheduling options plus a free retake for students to refresh the material.
Fullstack Academy has an Online AI & Machine Learning Bootcamp for data professionals who want to learn practical and theoretical machine learning concepts using real-world tools—graduating with the working knowledge and experience needed to qualify for a range of data roles, including those concentrated in AI. Students will also receive professional career coaching support for up to a year following graduation to help build and maintain an ideal, specialized career path in the industry.
Certstaffix Training offers two Python classes: Introduction to Python Programming and Advanced Python Programming. The first course covers data types, writing functions, mathematical modules, and string formatting. After the basics, the course moves into flow control such as loops, list comprehensions, enumerations, and is-is not operators. Finally, it takes a look at using virtual environments, command lines, and file processing to execute Python files. The advanced class covers lambda functions, mapping and filtering, sorting, plus mutable and immutable built-in objects. This course also introduces topics such as inheritance, attributes, methods, and properties. Students will learn to apply their new training by using an API to get data from a website, saving it into a CSV, and cleaning it up using Python.
Noble Desktop can help business owners who want to train or update their employees' coding skills with corporate classes. You can schedule sessions at your offices in a conference room with a remote instructor. Noble’s catalog includes introductory, bootcamp, and certification courses in Python, HTML, CSS, and JavaScript, or Noble can design courses to meet your company's specific needs.
Noble offers group class vouchers at a bulk discount, and employees can schedule individual classes according to their own schedules. Instructors are experienced industry professionals and attendees receive handouts, exam guides, and access to training videos to help them reinforce new skills. Find out how you can help your staff build their skills at corporate@nobledesktop.com.