Learn More About Data Science Classes in Phoenix
Data science is a field that incorporates a variety of disciplines, such as mathematics, computer programming, algorithms, and artificial intelligence, in order to draw insights from data. Professionals use the multifaceted field across industries to analyze data and make data-driven decisions, technological advancements, and solve problems.
Aspiring data science professionals, such as aspiring Data Scientists and Data Analysts, work to gain skills in alignment with the data science life cycle that will help them deliver projects and analysis to the companies or clients they work for.
What Can You Do with Data Science Training?
The scope of data science is expansive, with its uses applicable in healthcare, education, financial services, and other industries. Aside from Data Scientists, other roles use data science in their day-to-day responsibilities. Professionals in the healthcare industry create algorithms to create treatment plans for their patients. Data is also used to assess services offered by physicians and to manage the supply chain of offices and hospitals. In the financial industry, analysts not only use data to provide clients with financial advice; they also depend on data to detect fraud, draft reports, and create forecasts.
If you’re interested in a data science career and would like to attend a data science class, it’s important to know what you’d like to do with your data science training. Data Scientists and Data Analysts work extensively with data, creating visualizations and models, and analyzing data to provide effective business decisions. This requires a heavy background in mathematics, computer science, and statistics. Web Developers work with data as well, but their day-to-day work draws heavily on skills like programming and problem-solving.
What Will I Learn in a Data Science Class?
What you learn in a data science class depends on the type of class you enroll in. Data science classes tend to focus on a specific area of skills that data science professionals need, such as machine learning, programming, or data analysis. This may mean that you need to take several classes to advance your knowledge of data science. Data science bootcamps provide students with a great way to cover a wider range of skills during their training.
Machine Learning
Machine learning involves the use of data and algorithms to help artificial intelligence (AI) learn human behavior. Machine learning serves the general purpose of creating adaptable models that can perform complex tasks across industries. Common examples of machine learning include facial recognition, product recommendations, and email spam filtering.
To enroll in a data science course that covers machine learning, look for a data science bootcamp or a data science for machine learning class. Here, you’ll learn the fundamentals of machine learning, popular machine learning algorithms, and how to perform cross-validation.
SQL Querying and Python Programming
SQL and Python are programming languages commonly used for back-end web development. Both languages have several primary functions. SQL is a querying language that allows users to process and store information in relational databases, while Python is crucial for machine learning.
Data science courses that focus on web development and programming will teach you how to use these languages on the server-side, courses focused on data analytics will enable you to create data visualizations with the languages, and machine learning courses will cover how to run scripts with relational data.
Predictive Modeling
Predictive modeling is a statistical technique used to predict future behavior or outcomes. Predictive modeling finds applications in archaeology, the insurance and healthcare industries, and investment firms. Most data science classes cover the basics of predictive modeling. With this skill set, you can help companies improve their analytical capabilities.
Communication
Data science professionals need to have excellent communication skills. As part of their responsibilities, most must communicate their findings to colleagues. Their colleagues likely include individuals with little to no technical knowledge, so their communication skills must include the ability to disseminate information in layman’s terms. This requires clarity and concision, as well as efficiency when explaining.
Data science bootcamps often include hands-on group projects where students must work with their classmates. This hands-on opportunity provides you with the perfect chance to work on communicating in a team environment and then sharing your team’s findings with others.
How Hard Is It to Learn Data Science?
The difficulty level you face when learning data science depends on why you want to learn data science. Web development, machine learning, business analysis, marketing analysis, and financial analysis are all different aspects of data science that require different skills and knowledge. For the sake of efficiency, it’s important when you go into data science that you consider which aspects you’re most interested in learning.
What Are the Most Challenging Parts of Learning Data Science?
The field you enter and the skills you start with when learning data science greatly impact how challenging training is.
If you plan to work in web development, much of your training will consist of learning the appropriate programming languages and developing problem-solving skills. Aspiring Business Analysts and Marketing Analysts need to understand how to use data visualization tools such as Tableau and how to interpret data. If you want to work with AI and machine learning, you’ll need to focus heavily on developing strong skills in high-level mathematics and might only need basic skills in Python, Tableau, and similar programs.
Starting with little to no background in mathematics may make it challenging to learn machine learning. Likewise, if you have no experience analyzing data, a variety of fields that involve data analysis will take more time to learn. It’s important to know what prerequisites the field you’re interested in has before diving right into data science. It generally takes around six months to develop beginner-level data science skills, including the time you may require to learn the prerequisites of your field, such as statistics or probability.
Should I Learn Data Science In Person or Online?
When enrolling in a data science course, you typically have the option of in-person, live online, or asynchronous classes.
In-person classes follow a traditional learning style where students meet in a classroom and learn face-to-face. This setting encourages feedback from instructors and interaction between students. To enroll in an in-person class, you need to consider your schedule and see if schools in your area offer data science classes that you can attend.
Live online classes allow students to learn in a remote setting from a live instructor via a web conferencing platform. Live online classes follow a schedule like in-person classes do, but they remove the need to commute. Another type of online class is asynchronous classes. These classes allow students to access course material online and, more or less, self-teach. No instructor guides the class along, although class material may include recorded video lectures. This class type allows students to learn without having to disrupt their schedule, but the hands-off approach is best for highly motivated students who don’t need an instructor to teach the material as they would in a traditional classroom setting.
What Should I Learn Alongside Data Science?
To take your knowledge of data science to the next level, it’s recommended to learn several programming languages and data visualization tools, as well as brush up on statistical analysis. When learning data science, it helps to have a strong theoretical foundation, which you can build by learning statistics and probability. Programming languages like Python and R will help you take your mathematical knowledge and turn it into scalable computer programs.
Phoenix Industries That Use Data Science
Several industries in Phoenix depend on data science professionals to innovate and grow. If you have data science skills that you’re looking to put into use, consider the career opportunities these industries offer.
Education
Phoenix is home to over 19 postsecondary institutions that serve as major employers in the city. Educational data science in K-12 and postsecondary schools is responsible for the keeping of educational records, offers potential modeling tasks, and provides educators with the tools necessary to create data visualizations for easily digesting information.
Financial Services
Known as the country’s sixth-largest financial capital, the financial services industry dominates the local economy of the Phoenix area. Wells Fargo, Northern Trust, and FinTech, along with other financial services giants, offer services to the residents of Phoenix. The financial services industry depends on the field of data science to predict risk, protect its clients from fraud, and report on internal expenses.
Leisure and Hospitality
One of Phoenix’s most prominent industries is leisure and hospitality. Museums, shops, recreation, and a desert landscape draw in over $5 billion annually in tourism revenue, along with supplying over 200,000 jobs around the state. This industry uses data science for predictive analytics, which can provide insight into market trends, customer behavior, and operational efficiency.
Data Science Job Titles and Salaries in Phoenix
Interested in starting a career in data science? Depending on your skill set and interests, a wide variety of career opportunities await you. If you want to work closely with data, using data science principles in your everyday tasks, consider applying for a position as a Data Scientist. Data Scientists may specialize in AI or data analytics. As part of their job, they often create algorithms and models that they then use to find data-driven solutions for their company or client. The average annual salary for a Data Scientist in Phoenix is $128,000.
Want to dive deeper into data science? Machine Learning Engineers are a type of Data Scientist who works on training computers through datasets and algorithms. Their focus is on helping automate machines across industries, from healthcare to transportation. In Phoenix, a Machine Learning Engineer receives an average annual salary of $158,000.
Data Science Classes in Phoenix
Whether you’re interested in taking a data science class in-person or online, there are a great number of classes, bootcamps, and certificate courses that will help you become proficient in data science and its many related topics.
Noble Desktop, an educator based in New York City, offers several data science classes for Orlando residents to take live online. The Data Science & AI Certificate is intended for those looking to pursue entry-level Python engineering or data science positions with their training. This beginner-friendly program begins by teaching students the basics of Python programming and how to use its science libraries for data analysis. Participants also explore how to create machine learning models and study their performance. Learners create data visualizations like dashboards and deploy these projects online using GitHub. All participants receive six 1-on-1 mentoring sessions as well. Registration for this class includes enrollment in Noble’s Python for AI: Create AI Apps with Flask & OpenAI at no additional cost.
Noble also has a Python Machine Learning Bootcamp for those interested in focusing their studies on this popular coding language. Students begin by studying logistic and linear regression. They then learn algorithms like random forests and decision trees. Participants receive instruction on how to use machine learning algorithms to solve real-world problems. The mathematical foundations for machine learning algorithms will be visually explained to students, which does not require formal math training. However, participants should know how to work with Python and its data science libraries as a prerequisite to enrolling. All Noble classes include a free course retake for up to a year.
Data Science Corporate Training in Phoenix
Companies and organizations interested in team data science training can contact Noble Desktop about their corporate training options. Training is available live online with real-time instructors and onsite at your offices. Noble allows companies to customize their curriculum or choose from existing courses.
Group class vouchers are available for teams signing up for corporate training with Noble. Employers may select which courses to offer to employees, who can then attend training that fits their schedule. For more information about group vouchers or questions about Noble Desktop’s corporate training options, email corporate@nobledesktop.com.
Learn From Noble Desktop’s Experienced Data Science Instructors in Phoenix
Phoenix professionals have a lot of opportunities when it comes to expanding their knowledge in fields like tech, design, business, and data. Anchored by major businesses in downtown Phoenix and the surrounding areas, such as Tempe, Mesa, and Scottsdale, the city benefits greatly from a diverse economy that spans industries ranging from local government and education to tech and finance, all while maintaining strong connections to the global market. With more industries turning to data-driven solutions to make business decisions, learning data science in a place like Phoenix makes total sense. It's the best way to solve problems, extract insights, and keep things running smoothly across the entire organization. Through Noble Desktop’s network of professional instructors, students in Phoenix can access high-quality training that helps them meet the industry standard. With decades of combined experience, these instructors go beyond the basics and blend practical guidance with real-world insights. This helps students not only acquire technical skills but also the confidence to make it in their professional careers.
Deanne Larson
Dr. Deanne Larson is a data science and analytics expert with 20 years of experience and counting. She has worked as an advisor for Fortune 500 companies and FinTech organizations through her firm, Larson & Associates LLC. Throughout her career, she has been drawn to work with AI-driven strategies and initiatives, machine learning implementation, and customer data platforms. Additionally, Dr. Deanne has worked on fraud detection models and managed global personalization platforms that have served hundreds of millions of customers. She is also a knowledgeable instructor, having worked for City University of Seattle, where she mentored doctoral students and developed curricula in data and business analytics. Dr. Deanne currently teaches courses in subjects ranging from data and project management to AI and Python.
Geno Sexton
After 34 years of federal service, Geno Sexton retired in 2012 and now works as a Phoenix-based project management instructor. Throughout these decades, Geno worked for eight years in the Senior Executive Service, culminating as Deputy Chief Human Capital Officer and HR Director at the U.S. Department of Labor, where he led 120 HR professionals serving 18,000 employees. He was named Deputy CHCO of the Year in 2011 and served as the first HR Officer at the new DHS Headquarters. In his distinguished career, Geno has made a real impact and currently teaches project management courses. He is a Vietnam-era Army veteran, holds a Bachelor’s degree in Journalism and Mass Communications and a Master’s degree in Government from New Mexico State University, and is a proud bilingual and ESL-certified instructor.
