Discover the Best Data Science Classes Near Me
The field of data science is a relatively new field that’s an offshoot of two other fields: data mining and statistical analysis. Data Science is the process of using scientific principles and advanced data analysis to locate key information from within vast stores of data. This information is useful to those in an organization for decision-making and planning purposes. The data insights uncovered by Data Scientists play an integral role in business operations. They can improve a company’s efficiency, create more effective sales or marketing initiatives, and spot promising business opportunities. These data insights also help the organization have an edge over its competitors. The field of data science draws from a range of disciplines and skills such as data preparation, data mining, machine learning, data engineering, software programming, predictive analysis, statistics, math, and data visualization. Data Scientists generally work with all five data science life cycle stages. They capture data, maintain it, process it, analyze it, and communicate their data findings to other relevant stakeholders. Data Scientists are typically highly valued within their organization for their contributions and are paid competitive salaries. It remains an in-demand profession across industries.
Best Data Science Classes & Schools
Over a decade ago, The Harvard Business Reviewlisted data science as the “sexiest job of the twenty-first century.” As more data than ever before is created each day, the need for qualified data professionals is high and is expected to remain this way. Without Data Scientists, all types of organizations, particularly large ones, would find it harder to make data-driven decisions. These professionals play an important role in their organization because they extrapolate collected data and identify patterns or trends that affect different areas of their operations.
Most current industries are driven by data. Data Science is considered the driving force that powers today’s industries. Most organizations leverage data to stay competitive; they use it to optimize performance, expand operations, and provide customers with the best services and products possible. Those who study data science must be well-rounded individuals with a background in computer science, math, statistics, and programming languages like R and Python. Because these professionals must be skilled in a range of tools and languages, they are generally well-compensated. Pursuing a career as a Data Scientist can be a lucrative professional trajectory with many opportunities for upward career mobility across professions and industries. Generally, Data Scientists are paid significantly higher salaries than those in other management or IT sectors. With this higher compensation comes the expectation from employers that Data Scientists will be driven to work hard for their organization and be thorough when handling data. As new machine learning technologies emerge, data science is expected to be a career that will continue to be popular into the future and will continue to evolve to help organizations get the most out of the data they collect.
Best Data Science Classes & Schools
If you’re interested in studying data science, you can search for in-person data science classes and schools near you to find coursework most suited to your learning needs. The following sessions explore some upcoming in-person study options from top educational providers.
Digital Workshop Center—Data Science Certificate Program (Live Online)
Digital Workshop Center’s Data Science Certificate Program is available for those who want to learn data science through interactive virtual training. Participants study how to clean and organize data, identify important data features, and plot data. Instruction is provided on working with R software and using basic linear regression. Those enrolled study descriptive and predictive statistics. This course covers how to automate repetitive tasks, create automated reports, and use statistics to perform a range of daily business tasks. Students have the option of completing a capstone project to demonstrate real-world applications of their data science training.
Tuition is $5,995. This fee includes one-on-one mentoring in which students work with a career coach on professional development such as resume work. Tuition also includes workshops on the data science job search. A free month of support following the completion of the class is included with tuition, as is a free course retake for up to a year. Students should know core programming concepts like variables, functions, and data types as a prerequisite to study. They also should have intermediate-level Excel skills and know how to work with PivotCharts and PivotTables. It’s also recommended that class participants be familiar with how programming can be used in a business environment. This program takes most learners approximately 3-4 months to complete.
Noble Desktop—Python for Data Science Bootcamp (NYC & Live Online)
Python for Data Science Bootcamp, available from Noble Desktop, teaches students a range of Python skills needed to analyze data. Students begin with basic Python programming concepts such as how to write basic expressions and statements, work with different data types and lists, create variables, and use functions and methods. After mastering Python fundamentals, learners progress into more complicated Python skills, like working with dictionaries, lists, tuples, and strings. The second part of this class teaches participants to work with conditional statements and various control flow tools. Those enrolled receive instruction on Boolean Operations, If/Else statements, and loops. Part three of this class provides instruction on data science operations and tools. Students are taught to use Pandas and NumPy to import and clean data. They also study how to wrangle data and use Pandas data frames. Instruction is also offered on how to create data visualizations like histograms and bar charts, as well as fundamental statistics and data workflows. Next, students progress to Python machine learning and become familiar with how to create machine learning models.
Tuition is $1,495. This course is available in-person in New York City, as well as in the live online format. In addition to 30 hours of hands-on instruction, students receive a digital certificate of completion. All participants can retake this class for free for up to one year.
Elephant Scale, Inc—Google Cloud for Data Scientists (San Jose & Live Online)
Those interested in learning how to work with one of the leading data science platforms can enroll in Elephant Scale’s Google Cloud for Data Scientists. This course teaches students how Python can be used for data science, as well as Google Cloud’s specific data capabilities. Participants in this class learn how to use Google Cloud storage and compute engine. Training is provided on visualizing data with Google Data Studio and using Big Query to perform SQL queries. Students are also taught how to use Python for data analytics and how to run Python code on Google Cloud. The target audience of this course is those who work as Data Scientists or Data Analysts, as well as individuals interested in pursuing a career in these fields.
Tuition is $150. As a prerequisite, students should have a basic interest in data science. It’s recommended that learners have a basic understanding of Python and some general programming experience. All students must have a laptop or computing device with an unrestricted internet connection. It’s also recommended that those enrolled have a Google Cloud account.
UCLA Extension—Data Science Fundamentals (Los Angeles)
Data Science Fundamentals is available from UCLA Extension and is intended for those who are new to the field of data science. Students learn through hands-on exercises how data science can help an organization’s decision-making process. This program provides instruction on basic Python programming skills, statistics, and data analytics. Participants also work with common data science tools like Excel, SPSS, and Python.
This course costs $1,095. It takes approximately 11 weeks to complete this program. This course is open to all learners, and no prerequisites are required.
NYC Data Science Academy—Data Science with Python: Data Analysis and Visualization (NYC)
NYC Data Science Academy’s Data Science with Python: Data Analysis and Visualization is available for those interested in learning how to use Python to analyze and visualize data. Students in this class study how to work with different Python data structures, as well as Matplotlib, NumPy, and Seaborn, for data analysis and visualization. Unit one of this class introduces Python and teaches students the basics of its syntax and how to work with objects. The second unit covers topics like object-oriented programming, running Python scripts, using processing strings, and handling files. Unit three focuses on using Python for scientific computing. Data visualization is taught in the fourth unit.
The cost of study is $1590. This class takes approximately five weeks to complete. As a prerequisite, it is suggested that students interested in enrolling be familiar with common data structures such as dictionaries and lists, in addition to common data types, like string and numeric. Learners should also understand for/while loops. Participants in this program are evaluated on a pass/fail system; those who finish 80% of the homework and complete 85% of classes are eligible to earn a certificate of completion.
EGIS Associates, Inc—Python for Data Science (Denver)
Python for Data Science, provided by eGIS Associates, provides students with beginner-level content on how Python can be used for data science. Students in this class learn by doing and complete a range of examples that help them practice Python. The curse begins with an overview of Python’s history and main features. Students then learn how to install and configure the language, as well as how to run scripts. Instruction is offered on assigning data and creating variables. Participants learn the core data types such as objects, tuples, numbers, lists, dictionaries, and strings, and work with decision-support statements. Those enrolled also become familiar with how to manipulate datasets using Pandas.
No prerequisites or prior programming knowledge is required to enroll in this class. This program costs $760.
The Flatiron School—Data Science (NYC)
Data Science, which is available from The Flatiron School, is a comprehensive program in which participants study the data science skills necessary to pursue a career as a Data Scientist. Those enrolled study how to apply statistical analysis to data to find answers to questions, gather data, and locate actionable insights from data. This program includes an advanced Portfolio Project where students showcase their technical proficiency and data science skills. The Portfolio Project also provides an excellent way for those enrolled in this program to impress potential employers with their professional portfolio. This course also provides students with the opportunity to work in groups of two or three for the final three weeks of class to complete a large-scale project on data science and machine learning.
Tuition is $16,900. This course takes 15 weeks to complete. Tuition includes access to a network of employers and weekly one-on-one sessions with a career coach. In addition, this course comes with a money-back guarantee; those who complete this program and do not receive a job offer within six months are eligible for a full tuition refund. No prior data science experience is needed to enroll in this program. However, coursework progresses at a fast pace, and students are expected to have a familiarity with data science to succeed in this class. All learners have access to an introductory class, which is free, so they will be able to keep up with lessons.
BrainStation—Data Science Certificate (NYC or Live Online)
Data Science Certificate, which is offered by BrainStation, teaches students various data science skills required for end-to-end statistical analysis. This certificate program is taught in units. Unit one teaches students core Python programming concepts and skills, like how this language is used for analyzing and manipulating data. Students also are taught how to work with Python’s NumPy and Pandas libraries. The second unit prepares students to wrangle and clean data. Unit three covers how to apply statistical concepts to the decision-making process within an organization and how to model data. Unit four is devoted to machine learning techniques and algorithms.
Tuition is $3,250 for this certificate. It takes 30 hours to complete this program. Flexible payment plans, as well as scholarships, are available. Because this is an intermediate-level certificate, as a prerequisite, students should have experience working with Python programming and know basic statistical concepts.
Industries That Use Data Science
Data science is a tool used in many industries around the US such as healthcare, cybersecurity, entertainment, automotive, and agriculture. The following sections will take a closer look at the role data science plays for professionals who work in these industries.
Healthcare
The healthcare industry relies heavily on data. Nearly a third of the world’s data volume consists of healthcare sector data such as e-health records, clinical trial information, and disease registries. To help healthcare organizations optimize these data, Data Scientists are currently in-demand in the healthcare industry. These professionals perform tasks like searching for anomalies in patient data, designing wearable devices, and performing predictive testing.
Banking, Financial Services, and Insurance
Another industry in which those with data science training are in-demand is the banking, financial services, and insurance (BFSI) sector. In recent years, these fields have seen a sharp increase in use cases that create data that must be analyzed so it can be used. Finance professionals rely on data science skills to help inform their decision-making process and optimize customer data to extract actionable insights from this information. AI, along with data science, helps financial institutions perform more efficiently and offer better services to their clients. Data science helps with a range of tasks such as risk modeling, lending appraisal management, fraud detection, customer segmentation, lifetime value prediction, securing customer data, and algorithmic trading.
Government
Big data plays a significant role in the public service industry. Many government positions rely on those with data science training to perform tasks like health research, financial market analysis, energy analytics, environmental protection, and fraud detection. The Social Security Administration uses big data analytics to study huge numbers of disability claims each year. Those with data science skills are also needed to spot suspicious or fraudulent claims. In addition, the FDA relies on data to spot and study trends relating to diseases or food-related illnesses to mitigate their spread.
Cybersecurity
Cybersecurity professionals are hired to prevent cybercrime and implement measures to safeguard their organization from future threats. Data Scientists are often involved in their efforts by designing models that can understand malicious activity patterns and predict them with enough training. There is currently a high demand for Data Scientists in the cybersecurity sector since cyberattacks are becoming more prevalent and difficult to detect. More companies are hiring Data Scientists to help find cybercriminals and prevent them from causing further damage.
Entertainment
Streaming entertainment providers like Netflix, Spotify, and YouTube rely on user data to provide customized recommendations for songs, movies, TV shows, and other forms of entertainment. To keep up with customer demand, there’s a greater need than ever for these organizations to employ Data Scientists to better meet customers’ needs and provide the most relevant content to subscribers. Those with a background in data science help these entertainment providers get the most out of their data. They gather, process, analyze, and store users’ data and use it to offer recommendations that can help their employer provide more personalized services to a wider audience base. With the help of data science strategies like AI and machine learning, Data Scientists ensure that the content suggested to subscribers will keep them engaged and interested in continuing to use the platform.
Automotive
In the automotive industry, data science is used for many purposes. It is a valuable skill set that can help streamline research, design, and marketing efforts. With the help of advanced analytics, Data Scientists who work in the automotive sector have created autonomous automotive systems and their various components such as cameras, sensors, global navigation satellite systems, radar, light detection and ranging tools, and internal navigation systems. Professionals with data science training use cognitive IoT to improve vehicle safety. They also can more effectively create and manage schedules. Data Scientists can propose solutions to reduce the cost of automotive repair, speed up production lines, use predictive maintenance to spot any product defects and grant greater control to manufacturers who work with supply chains. As automobile design grows more complicated and can gather more data, data science is essential for keeping track of variables like fuel efficiency, travel routes, mileage, and wear and tear. Data science is also expected to help this industry continue to expand as new technologies are developed that will enable cars to communicate with one another and perform more autonomous tasks.
Oil and Gas
One of the largest and most lucrative sectors worldwide is oil and gas. This industry alone accounts for $3 billion in daily revenue. Data Scientists who work in this industry look for insights into big data to help their organization perform daily tasks more efficiently, cut down on errors, and reduce maintenance costs. To do so, these professionals use information that isn’t used in other industries such as well logs and data pertaining to drilling. Data Scientists interested in working in oil and gas have to have a commanding knowledge of how basic operations in this sector are performed. They must also have specific technical skills to run simulations and carry out experiments.
Telecommunication
Data science has a range of applications in the telecommunication industry. Telecommunication involves electronically transmitting information from one physical location to another. The transmitted information can take several forms such as telephone calls, video, data, images, or text. Telecommunications are also useful for integrating remote computer systems into networks. This industry creates huge amounts of data each minute, consisting of customer information, network data, and call details. Data Scientists in telecommunication must have the skills to leverage all these data. This requires extensive domain knowledge, as well as well-rounded training in the various areas of data science, which may differ depending on the employer.
Agriculture
Although it may not be the first industry that comes to mind when you think of data science, professionals with data science training perform a range of tasks in this sector such as analyzing crop yield, soil, or weather patterns to ensure production values are in keeping with estimates. They also help companies create scalable pipelines that can be automated. Data Scientists tasked with predicting plant disease or weather patterns can create machine learning models with the ability to do so.
Retail
To remain competitive in a volatile economy, retail providers seek Data Scientists to provide insights into the products their customers want and need and how best they can provide them. Around the world, retailers look to Data Scientists to help them cut down on loss, improve production, and ensure their customers are provided with the best products.
Data Science Jobs & Salaries
Now is a great time to pursue a career in data science. Currently, there are over 10,000 job openings for those with a background in data science are currently listed on Indeed. This field is relatively young, which means that there is a need for qualified professionals to help organizations get the most out of their data. Data Scientists are currently listed as the sixth-best tech job in the US. Not only are Data Scientists in-demand now but this field is expected to continue to be in-demand for at least the next decade and experience a 36% growth rate from 2021 to 2031, which is well above the national average. The following sections will take a closer look at some of the job opportunities available for Data Scientists and how pay rates vary for these professionals depending on where they work. Often, higher salaries are available for Data Scientists who work in large cities due to a higher cost of living.
Database Administrator
Database Administrators are hired to make sure a company’s databases are performing efficiently. Their job involves organizing and designing systems capable of safely storing various data types such as customer shipping records or financial information. Database Administrators also make sure authorized users have access to the data they need and that it can be easily retrieved. In addition, they back up data and offer support and training to database users. These professionals typically work with Developers to troubleshoot issues and create and implement new database features. Database Administrators have to have a background in business, as well as technical training, to best provide their organization with the tech support needed to satisfy its business needs.
The average salary for a Database Administrator in the US is currently $85,000. Those who work in Cleveland earn just above this national average of $85,000. In Portland, Database Administrators earn close to $90,000. Pittsburgh-based Database Administrators also earn $90,000 yearly.
Data Warehouse Manager
Data Warehouse Managers oversee a team’s progress as they create, implement, maintain, and provide support for various data warehouse projects or systems. Their job also entails monitoring how data repositories and data architecture are designed. Data Warehouse Managers also organize, store, and analyze data systems and data. These professionals must ensure these tasks are carried out in such a manner that maintains confidentiality and security, and is in keeping with their organization’s deadlines.
Throughout the US, Database Warehouse Managers generally receive high salaries. The current average pay for these professionals is $145,000 a year. In Cleveland, these professionals make slightly less than a $140,000 salary. Portland-based Database Warehouse Managers also make approximately $140,000 a year. In Pittsburgh, these professionals can expect to earn above the national average and make around $150,000 yearly.
Data Scientist
Although the role of a Data Scientist will vary depending on the employer, these professionals determine which driving questions their organization has that are most pressing to answer. They then seek out related data to propose answers. Businesses employ Data Scientists to source, organize, and analyze vast amounts of unstructured data. To do so, these professionals must have a range of skills such as analytics training, business knowledge, and data skills like how to mine and clean data, as well as how to share data findings in presentations. A good portion of a Data Scientist’s day may be spent performing research. They also write code and create algorithms designed to find answers to a given dataset.
Because data science is an in-demand profession, pay rates for Data Scientists are typically high throughout the US. The average salary for Data Scientists in the US is $125,000. Those employed in Cleveland make approximately $125,000 a year. In Portland, Data Scientists earn slightly above the national average and can expect to make just over $125,000 yearly. Pittsburgh-based Data Scientists make a yearly salary of $130,000.
Statistician
Statisticians are employed by an organization to apply statistical models and methods to any problem their organization faces. This requires them to collect and analyze data, then communicate their findings to organizational stakeholders, who can use it to inform their decisions. The role of a Statistician has changed in recent years. In the past, these professionals were hired in fields like research and academia. Now, because of how much data is being created and collected across industries, businesses seek Statisticians to help them optimize their data so it can be used to help them make more informed decisions. Statisticians are needed in many industries such as healthcare, the physical sciences, business, government, and environmental sciences. Although the professional responsibilities of a Statistician vary depending on the employer, they commonly complete tasks like spotting trends, patterns, or relationships in datasets, providing recommendations on business strategies or organizational operations, and creating processes to collect data.
The average salary in the US for Statisticians is $85,000. Cleveland-based Statisticians make about the national average and can expect to earn just above $85,000 yearly. Pay rates for Statisticians in Portland are also in keeping with the national average of $85,000 a year. In Pittsburgh, Statisticians make a salary of $90,000.
Database Manager
Database Managers manage huge volumes of data for their employers. Companies hire these professionals to help ensure their database systems continue to perform their functions smoothly and protect the privacy of the data they contain. Database Managers not only maintain database systems but also develop them as well, which entails implementing various security programs to keep data safe. They must stay apprised of the most current developments in how databases are designed and install and test new software. These professionals also work to safeguard database systems against possible threats like electrical storms. They also devise disaster recovery solutions, configure hardware, install software updates, troubleshoot problems, and keep accurate records of any repairs and installations they have completed.
On average, Database Managers earn a salary of $80,000. Those who work in Cleveland make slightly more and can expect to be paid nearly $85,000 a year. Database Managers employed in the Portland area make around $80,000 a year. In Pittsburgh, these professionals are paid nearly $90,000.
What Will I Need to Learn Data Science?
Learning data science is a choice that can open many professional doors and lead to higher-paying roles. If you’re interested in studying data science, you must be motivated to learn a range of skills, programming languages, analytical tools, and techniques that will prepare you to work with data. Most Data Scientists work with several programming languages such as Python and SQL, for organizing unstructured data. Therefore, you will need to study these languages. Python is free and open-source, and MySQL is an open-source database system. Additionally, because Data Scientists regularly analyze and display data, it’s also important to have access to Microsoft Excel when studying data science. You likely will also need to have access to analytical tools like SAS or Hadoop, which are useful for finding relevant information from within organized datasets. Those who enroll in in-person coursework are usually provided with the tools needed to work with large datasets.
In addition to downloading programs like Excel and having access to programming languages like Python, those interested in studying data science should also have a background working with statistics, multivariate calculus, and linear algebra. If you don’t have training in these fields of advanced mathematics, you may need additional study guides and tutorials to help them acquire this knowledge. A range of soft skills is also helpful for becoming a Data Scientist such as an analytical mindset, critical thinking, the ability to clearly communicate information to stakeholders, and an understanding of how businesses work. While these can be covered in a classroom setting, they are often acquired through practice and training.
Is It Difficult to Learn Data Science?
You may be wondering how hard it is to learn data science. This multidisciplinary field requires that students study a range of skills and disciplines such as computer programming, linear algebra, machine learning, business, statistics, and mathematical modeling. Because it requires so many advanced skills, some consider data science a relatively challenging field to learn. In addition to this skill set, becoming a successful Data Scientist also requires that individuals possess domain knowledge relevant to their specific field of employment. For example, those who work in marketing must have a full understanding of the available advertising channels, their cost, and how they work. Because of the collaborative nature of data science, to succeed in this field, you must also acquire clear communication skills to regularly interact with Software Engineers, other Data Scientists, Data Analysts, managers, and executives. The iterative nature of this field also requires that Data Scientists be willing to try solutions multiple times to see whether they’re effective. This requires developing patience, perseverance, and understanding that there may be multiple solutions to any problem. Although it takes time and training to fully master the various skills needed for data science, those devoted to their studies can succeed and become well-rounded Data Scientists.
