Explore machine learning by applying Python to predictive modeling and automation. Learn to make data smarter through algorithmic design and critical analysis.
Master Python for data analysis, machine learning, and automation. Build predictive models, create dynamic dashboards, and unleash the power of data visualization. Launch your career in data science and Python engineering, equipped with Python, NumPy, Pandas, and Matplotlib.
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 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.
Machine learning is a subset of artificial intelligence that allows programs to use past data and experience to learn and optimize performance. In other words, machine learning programs can “think” and generate solutions based on experience without the direct input of a programmer.
You’ve likely interacted with machine learning in the past without realizing it. Streaming services like Spotify are a great example. As this app gains more data about your personal preferences, it is better able to make relevant music recommendations for you. When you interact with the program by “liking” a song, you provide more data that it then uses to make future recommendations.
Python and data science are closely related subjects to machine learning. You can learn more about Python classes in San Francisco as well as data science classes in the area.
San Francisco is known for its tech industry, with many claiming the city is the epicenter for tech advancement. Machine learning is used across many products and services, from AI research to applied machine learning platforms. For instance, OpenAI is based out of San Francisco and hires machine learning pros to develop large-scale language and multimodal models. There’s also a huge hub for robotics in San Francisco, with companies like Cruise and Zoox applying computer vision, sensor fusion, and machine learning to enable autonomous motor vehicles.
The finance industry in San Francisco deploys machine learning to improve financial services for the customer and the back-end processes that the finance professionals handle. For instance, it’s used for risk assessment and fraud detection to help banks and investment professionals give their clients the most accurate and informed choices for financial security. Likewise, it’s used to verify the user’s identity so that no one else can access sensitive financial information. For instance, Chime uses machine learning for fraud protection, customer insights, and product personalization, which instills trust within the consumer and boosts the company’s overall ethos.
Healthcare and biotech companies in San Francisco use machine learning to accelerate drug discovery or improve diagnostics. It’s also used to personalize patient care. For instance, Tempus applies machine learning to clinical data to help doctors make more well-informed treatment decisions, particularly in oncology. Insitro may use machine learning models to identify new drug targets and reduce the cost and time of these pharmaceuticals. Overall, machine learning helps this industry by streamlining time-sensitive processes, thereby improving the patient experience and outcomes.
San Francisco is home to a large number of tech and social media companies, including Facebook, Google, Airbnb, X (formerly known as Twitter), and others. Given the role machine learning can play in these businesses, this is an in-demand skill for careers in San Francisco.
Individuals with machine learning skills can pursue careers as Machine Learning Engineers, Data Scientists, and Data Engineers. Given the high cost of living in San Francisco, each of these roles makes more on average than in the United States as a whole. Machine Learning Engineers can anticipate the highest typical yearly salary of the three roles, at around $198,000 per year on average. Data Engineers bring home about $157,000 per year, and Data Scientists make $157,000 on average.
Live online courses are a great way to learn about machine learning from the comfort of your own home or office. Virtual courses are interactive and allow you to ask your instructor questions and receive feedback in real time, just as you would during in-person training.
Noble Desktop offers several virtual classes that cover machine learning. In particular, its Data Science Certificate prepares individuals for careers in data science and Python engineering roles. In this program, students learn Python programming fundamentals, including how to build machine learning models.
Noble also has two courses dedicated specifically to machine learning. Its Python Machine Learning course requires that students are already comfortable with Python and data science libraries (NumPy and Pandas) to participate. The course covers the skills required to solve real-world problems using machine learning.
Its Python Data Science and Machine Learning Bootcamp teaches students how to code with Python, as well as use NumPy, Pandas, and Matplotlib. Students will also use machine learning packages like scikit-learn to create predictive models. This course meets for 66 hours, and students can choose between daytime and evening formats.
Professionals looking to upskill or reskill may be interested in Noble Desktop’s corporate and onsite Machine Learning training. This training can be held at corporate offices or live online using a teleconference platform like Zoom. Companies can choose from Noble’s existing courses or request custom-made training to meet an organization’s unique training needs.
Additionally, companies can purchase vouchers for Noble’s open enrollment group classes. Your company will receive a discount if multiple vouchers are purchased. If you’d like to learn more about corporate and onsite training, don’t hesitate to reach out through email.
If you’re searching for professional opportunities in fields related to tech, design, business, and data, look no further than San Francisco. The city is a global hub for innovative technologies, startups, and financial institutions, with some big-name companies like Google and Wells Fargo calling the Bay Area home. Machine learning is one branch of artificial intelligence that is growing exponentially around the country, but especially in San Francisco. By learning to power technologies such as chatbots, recommendation systems, and fraud detectors, you can make a real difference in a number of fields. Through Noble Desktop’s quality instructors, you’ll be able to start your career in one of these fields quicker than you think. Their combined decades of experience give professionals and aspiring experts the skills that they’ll need to excel in a real-world setting without having to sacrifice hands-on learning. It’s an ideal place to find training that teaches technical skills and practical applications to serve you well in the job search and beyond.
As an experienced educator, researcher, and conference speaker, Dr. Deanne Larson brings her industry experience to the classroom, often teaching classes related to data, AI, Python, and project management. Her professional career is exceptional, beginning with her earning three doctorates in Computer Science (AI), International Management, and Management, as well as a Master’s in Business Analytics. Beyond academia. Dr. Larson has also worked in the field of data science and analytics for over 20 years, serving as an advisor to Fortune 500 companies, global enterprises, and FinTech startups through her firm, Larson & Associates, LLC. Her work spans AI-driven strategies, fraud detection machine learning models, and data governance solutions in cloud and blockchain environments. Her extensive training and career accomplishments give her the credibility to impart her knowledge to her students.