Data Analytics Classes Live Online: Best Remote/Virtual Data Analytics Training

Data Analytics Certificate Learn The Skills Guarantee™

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 more & register Explore Noble Desktop’s Data Analytics courses
- $4,995
- 156 hours
- Free retake
- Live Online or NYC
- 1:1 Mentoring Included
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Noble Desktop Data Science & AI Certificate

In this comprehensive data science program, individuals will learn a variety of critical skills to become a data scientist. Students will learn to code with Python, create machine learning models, automate tasks like web scraping, and interact with databases using SQL. Topics include data analysis with Python's Numpy and Pandas packages, data visualization, predictive analytics, machine learning, SQL querying, Python automation, and web scraping. Students will learn hands-on by working in Python and SQL and will complete the program with the skills they need to enter the field of data science. This program offers flexible scheduling and provides a free retake for students to refresh the material.
- $3,995
- 114 Hours
- Weekdays or Evenings
- Beginner
- Free Retake
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General Assembly Data Analytics Bootcamp (Online)

Learn to problem solve, and effectively communicate, like an analyst. This course teaches you to use industry-standard tools to make ethical, data-driven decisions. Experience hands-on training to master SQL, Excel, Tableau, PowerBI, and Python – tools listed in virtually every data analytics job posting across industries.
- $16,450
- 12 Weeks
- Weekdays or Evenings
- Beginner
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Fullstack Academy Online Data Analytics Bootcamp (Full or Part Time)

Students build in-demand industry skills and prepare to take certification exams in Tableau and Amazon Web Services. The program consists of Fullstack’s live online classes and workshops so you will feel fully supported along your journey. The up-to-date curriculum ensures course activities are relevant with real-world applications and interactive technology to help you master the knowledge and skills that you’ll acquire throughout the program.
- $14,495
- 10 Weeks
- Weekdays
- Beginner
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Noble Desktop Python for Data Science Bootcamp

In this data science bootcamp, students will build programming skills and data analysis skills using Python. This course is open to beginners and is meant to get individuals up and running with Python programming and data science to generate insights from data. Topics covered include programming fundamentals, working with data frames, data analysis, data visualization, and statistical analysis. This course offers flexible scheduling options and a free retake for students to refresh the materials.
- $1,495
- 30 Hours
- Weekdays, Evenings, or Weekends
- Beginner
- Free Retake
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Thinkful Data Analytics Flex

Data Analytics Flex is a 6-month part-time program designed to get you a job as a data analyst. You will begin by learning how to master Excel and storytell with Powerpoint. Afterwards, you'll learn how to query data using SQL and visualize data using Tableau. Once you've mastered these building blocks, you'll receive business case studies to simulate real-world work projects and you'll also be exposed to statistics. Finally, you'll learn how to clean data using Python and work on your capstone project. This program comes with a tuition backed guarantee if you don't land a job within 6 months of graduation.
- $4,500
- 6 Months, 25 hr/wk
- Weekdays
- Intermediate
- Money-back guarantee
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NYIM Training Data Analytics Technologies Bootcamp

In this program, participants will learn the key skills and tools needed to succeed as a data analyst, including Excel, SQL, and Tableau. Attendees will learn how to use Excel to create graphs, summarize data with PivotTables, and analyze data. In SQL, attendees will learn the essentials of relational databases, queries, functions, and more. Finally, participants will learn Tableau to create visualizations to express their data. The program is open to beginners and has flexible scheduling options. Tuition includes hands-on training, a free retake, and training manuals for each course.
- $1,949
- 51 Hours
- Weekdays
- Beginner
- Free Retake
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NYC Career Centers Data Analytics Technologies Bootcamp

In this 8-day intensive Data Analytics bootcamp, students with little to no background in data analytics will learn how to use Microsoft Excel, SQL, and Tableau to summarize, display, and discover key insights hidden in data sets. By the end of this bootcamp, students will be able to use Excel to aggregate and summarize data, sort data with PivotTables, create charts and tables in Excel, use SQL to filter and sort large data sets, use advanced database queries, create visualizations with Tableau, and much more. Students will also be able to reinforce what they learn through the numerous projects they encounter throughout the course. This course also offers a free retake within six months to allow students to revisit any concepts needing to be refreshed and walk away with a much stronger grasp of the material.
- $1,949
- 51 Hours
- Weekdays
- Beginner
- Free Retake
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Thinkful Data Analytics Immersion

Data Analytics Immersion is a 4-month full-time program designed to get you a job as a data analyst. You won't have to pay until you get a job making at least $40,000. You will begin by learning how to master Excel and storytell with Powerpoint. Afterwards, you'll learn how to query data using SQL and visualize data using Tableau. Once you've mastered these building blocks, you'll receive business case studies to simulate real-world work projects and you'll also be exposed to statistics. Finally, you'll learn how to clean data using Python and work on your capstone project.
- $12,250
- 4 Months, 40 hr/wk
- Weekdays
- Intermediate
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Noble Desktop Python Machine Learning Bootcamp

In this course, students expand their 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. This will bring important statistical concepts to the forefront, such as bias, variance, and overfitting. Participants also learn how to measure the accuracy of your models, as well as tips for choosing effective features and algorithms.
- $1,895
- 30 Hours
- Weekdays
- Intermediate
- Free Retake
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Showing 10 of 288 courses

Key Insights

Organizations increasingly rely on big data analytics, leveraging real-time data collection and analysis to swiftly make informed strategic decisions and maintain competitive advantages.

Data analytics training typically covers essential skills including data gathering methods, programming languages (Python, R, SQL), statistical techniques, and visualization platforms (Power BI, Tableau) for presenting clear, actionable insights.

Data analytics ranks among LinkedIn's top ten most in-demand skills for 2024, reflecting the global shortage of qualified professionals capable of effectively managing and interpreting massive and growing datasets.

Learn More About Live Online Data Analytics Courses

Data analytics is the process of examining data sets to discover trends and patterns.

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Many different types of organizations rely on data analytics to help them better understand their business and customers and to make informed decisions about the future. One Data Analyst calls data analytics a “game changer,” explaining that it can help people do many different things more effectively. She explains, “It's incredible how much data can help take the guesswork out of decision-making. With the right approaches, you can solve problems or come up with possible answers to things that seemed like they might be mysteries with no clear answer.”

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People have been collecting and analyzing data for hundreds of years; however, the practice of data analytics as it exists today is a result of the invention of computers and databases, which allow society to collect and store large amounts of data. The United Nations explains that the world is generating massive and ever-increasing amounts of data. It says, “The volume of data in the world is increasing exponentially. This deluge of digital data is known as big data. Data is growing because it is increasingly being gathered by inexpensive and numerous information‐sensing, mobile devices and because the world’s capacity for storing information has roughly doubled every 40 months since the 1980s.” Not only are huge amounts of data being collected, but that data is also being analyzed for a variety of purposes. In recent years, data analytics has become more integral to life around the world, and as technology continues to advance, analysts gain more complex tools, and the ways they can use data continue to expand.

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The process of data analytics starts with the collection of data. After that, analysts clean the data so that it is ready to use, removing any data that is incorrect, duplicated, or unusable. Next, they analyze it using a variety of tools, including statistics and programming languages like R and Python. The final part of data analytics is sharing the results of the analysis. Data Analysts need to present their findings in a form that is accessible and easily understandable to other people—including non-experts—and often do so by creating visualizations with programs like Power BI or Tableau.

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Data analytics is sometimes categorized into four types: descriptive analytics, which involves describing what is happening in the data; diagnostic analytics, where analysts find patterns in the data; predictive analytics, which is the process of using data to make predictions about the future; and prescriptive analytics, where analysts use the data to make recommendations about actions that should be taken.

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What Can You Do with Data Analytics Training?

You can do a lot with data analytics training. One Data Scientist explains, “Data helps us make informed decisions by providing us with insights into various aspects of our lives.” He says that some of the ways data is used include diagnoses and monitoring treatments and outcomes in healthcare, making informed business decisions, personalizing education, and personalizing online and retail experiences. He says, “In summary, data plays a critical role in many aspects of our lives.”

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Analytics company SAS explains that businesses that use analytics gain many advantages. For instance, it says, “Some of the best benefits of big data analytics are speed and efficiency. Just a few years ago, businesses gathered information, ran analytics, and unearthed information that could be used for future decisions. Today, businesses can collect data in real-time and analyze big data to make immediate, better-informed decisions. The ability to work faster – and stay agile – gives organizations a competitive edge they didn’t have before.”

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Data analytics has become an in-demand skill, and experienced analysts are sought after by businesses in many different industries. According to an article on the LinkedIn Learning Blog, analytics is one of the ten most in-demand skills for 2024. The World Data Science Initiative also reports that data science skills are in high demand worldwide. It explains that this high demand is a result of the abundance of data and the shortage of people who know how to work with it. It says, “Organizations around the world are finding it a big challenge to handle the enormous amounts of data at their disposal, and an even bigger challenge is how to manage the future datasets that will be exponentially larger.”

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What Will I Learn in a Data Analytics Class?

There are many different types of analytics classes, and each class has a different curriculum; however, most data analytics classes also have some elements in common. For instance, almost every class covers the process of gathering data. No matter what class you take, you’ll also learn different ways of analyzing and visualizing that data, such as programming languages, statistical analysis, and analytics platforms. Another skill that you’re likely to learn when you take a data analytics class is communication skills, which are also important to being a Data Analyst, since this job involves communicating with others about what the data reveals.

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Gathering Data

One of the first steps in data analytics is to obtain data, and when you take a data analytics class, you’re likely to learn about some of the different ways to do so. You can collect your own data through surveys and software or by accessing publicly available information. Another very common way to get data is to use a database. A data analytics class will often include instruction on communicating with large databases and retrieving data.

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Using Programming Languages

Most Data Analysts use a variety of programming languages as a tool for working with data. For instance, SQL is a popular tool for communicating with relational databases. Python is another popular programming language that is often used by analysts. This versatile language is often used for statistical calculations and for creating visualizations. R is also a popular language used for data analysis. When you take a data analytics class, you’re likely to learn how to use at least one of these languages.

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Statistical Analysis

In order to analyze data, you’ll also need to learn about statistics, which is a branch of mathematics that involves collecting, analyzing, and interpreting data. Analysts use many different statistical methods when they work with data, and most data analytics classes cover some of the most popular methods.

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Analytics Platforms

When you learn data analytics, you’re also likely to learn how to utilize analytics platforms to share your data with other people. Analytics platforms are tools that can help you analyze and visualize your data and are particularly useful with large and complex sets of data. Tableau and Power BI are two common analytics platforms.

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Communication Skills

Part of data analytics is analyzing data; however, to be a good Data Analyst, you also need to know how to communicate your findings with other people. When you take a class, you’re likely to work on your communication skills in addition to your analytics skills. LinkedIn explains that there are six main types ::contentReference[oaicite:41]{index=41}

Communication Skills

How Hard is It to Learn Data Analytics?

Data analytics can be challenging to learn since it is a complex and technical field. It involves statistics and other high-level math skills, in addition to computer programming, and many people find it fairly difficult to master. Most experts say that one of the best ways to master this field is to start with the foundations and basic skills, making sure you have a firm grasp on these before moving on to more complex skills. Taking a paid class can also help speed up the learning process, since that way you can receive guidance from an expert. While data analytics can be challenging, with time and effort, almost anyone can learn it.

What Are the Most Challenging Parts of Learning Data Analytics?

Many people say that one of the most challenging parts of learning data analytics is that this career requires constant learning because data analytics technology is always changing. A recent LinkedIn post explains, “Data Science is not a static field; it is a dynamic and ever-evolving discipline. The tools, techniques, and methodologies used in Data Science are in a constant state of flux as new technologies emerge and existing ones evolve.” The fact that this field involves constantly changing tools, techniques, and methodologies means that when you work in data analytics, you’ll need to continually spend time learning to stay up to date on these new technologies. While this may be challenging, many analysts say that it also has a positive side, because constant learning also means that they don’t get bored.

How Long Does It Take to Learn Data Analytics?

The amount of time it takes to learn data analytics will vary according to how much related knowledge you already have, and how much time you can devote to learning and practice. Most experts say that you can get fairly comfortable with data analytics skills within about six months, but that getting to a professional level may take several years. If you already have some expertise with the tools used in this discipline such as statistics, programming languages, and data analytics platforms like Excel and Tableau, then you’re likely to learn more quickly. In addition, as with any new skill, the more time you spend practicing, the more quickly you’re likely to learn.

Should I Learn Data Analytics in Person or Online?

In-person and online classes are both popular ways to learn data analytics. Each class format has its own unique advantages and disadvantages, and the decision about which one to choose will depend on many factors including your learning style, your goals, and where you live. In-person classes are a popular choice because many people find them to be engaging, and also like the face-to-face interaction they get with the instructor and fellow students. In-person classes allow students to get immediate instructor feedback and also let them easily interact and network with other students. Some instructors say that it is also easier for them to understand student progress and see whether or not students need additional help when they teach this way. In addition, since an in-person classroom is specifically designed for learning, it typically has minimal outside distractions. However, in-person learning requires students to commute to the classroom, which can add extra expense and time. In addition, not every student lives in an area that has the in-person classes that they are looking for.

Some people find that a live online class is a better fit than an in-person class because there is no commute and they can choose from a wider variety of classes. Live online instruction takes place in real time, just like in-person learning does; however, rather than being physically present in a classroom, students attend by logging on via computer. They can still see and interact with the instructor, and the instructor can still answer questions and give immediate feedback. In many live online classes, interaction between students is also encouraged. In fact, some students prefer the live online format because they may get the opportunity to interact with a more diverse group of students, from cities all across the United States, or even from other countries. Some students also like learning online because they find it less intimidating than being in a classroom full of people. A downside to live online learning is that students typically need to supply their own equipment and software. In some cases, they may also have to deal with technical issues. In addition, while live online classes offer more flexibility than in-person ones, they still require students to attend class at a specifically scheduled time.

For students who need even more flexibility, an on-demand class can be a good option. On-demand learning is not live. Instead, students receive pre-recorded content and they learn at their own pace. This means they can stop and start whenever they need to and can even rewind content if necessary. With on-demand learning, students can choose to learn in small blocks or long sessions, or create any other type of learning schedule that works for them. A downside to this flexibility is that students need to be able to work independently. Depending on their learning environment, they may also face more distractions than they would in a classroom.

Can I Learn Data Analytics Free Online?

Data analytics is a complex field that requires extensive specialized and technical knowledge. Free online resources can be a good way to get an overview of this field, learn a new skill, or troubleshoot a problem; however, they are unlikely to provide more than this. If you’re serious about learning data analytics, you’ll probably want to enroll in a paid course. With a paid course, you’ll get guidance from an experienced professional who can guide you through a comprehensive program, answer your questions, provide feedback on your progress, and share insider tips and tricks. In addition, you can be sure that you’re learning up-to-date skills, which is particularly important in a field like data analytics where technology changes quickly. Another benefit of a paid class is that you’ll usually receive a certificate or other type of evidence of your learning, which you can add to your resume.

What Should I Learn Alongside Data Analytics?

While a career in data analytics will require that you master many different technical skills, soft skills can also be beneficial. Soft skills include things like the ability to communicate with others, teamwork skills, and adaptability. They are important because they can help you maintain good professional relationships, help work run smoothly, and help you avoid conflicts. A recent Forbes Council Member post explains, “Although hard skills are necessary, soft skills such as the individual’s personality, people skills and work ethics are also very important in a data analytics professional. Soft skills are essentially habits and characteristics that shape how one works and interacts with others.” According to the author, many employers say that it can be difficult to find individuals who have both hard and soft skills. In his opinion, the five most important soft skills for a Data Analyst to develop are communication, collaboration, critical thinking, curiosity, and creativity.

If you plan to work in data analytics, it can also be helpful to learn more about whatever industry you plan to work in. For example, if you plan to work in finance, you may need to gain an understanding of basic finance principles and practices. You might need to learn how to read financial statements like balance sheets and profit and loss statements, and understand core financial concepts like financial modeling and forecasting.

Industries That Use Data Analytics

Data analytics is used in many different industries. The University of Notre Dame explains that this is an extremely versatile set of skills. It says, “Data science is a very flexible field and can be applied across all types of industries. From banking and education to marketing and nonprofits, nearly every type of organization benefits from having a data science expert on their team that can explore, report on, and monitor data to make better decisions, improve performance, and meet goals faster.” Data analytics skills are used in many different types of businesses and are also used in public sector and nonprofit organizations. There are also many different specializations in data analytics such as database management, data mining, artificial intelligence, and business analytics.

Finance

Data analytics jobs are common within finance. Many different types of financial institutions use data analytics to help them make better decisions about how to manage and invest their money. Certification provider CompTIA explains, “In recent years, data professionals have become a key in transforming financial data into business insights not only to support stakeholders making better decisions but also to allow for a deeper understanding of metrics and key performance indicators (KPIs), appropriate examination of financial transactions, and predictive forecasting.” The United States has a thriving finance industry. For instance, according to a recent research report, commercial banking is its largest industry by revenue.

Tech

Data analytics is also widely used within the tech industry. According to the International Trade Administration, the United States has the world’s biggest tech market. The organization says, “The industry accounts for $1.9 trillion of U.S. value-added GDP (more than 10 percent of the national economy) and 12.1 million jobs.”

Public Sector Industries

Data analytics is also commonly used in the public sector. This includes industries like healthcare and government. Many public sector industries like these need to manage large amounts of data and analyze it so that they can make informed decisions. For example, government agencies analyze data as part of the process of creating public policies, and healthcare providers use it to help them provide better care. Some public sector industries rank among the largest employers in the United States. An example is the healthcare industry, which a Harvard blog article calls “one of the most essential and consequential parts of our economy.”

Retail

The retail industry utilizes data analytics in many different ways, including personalizing the retail experience for shoppers, creating products that consumers want, and designing effective marketing strategies. Analytics company SAS explains that analytics has become an important part of retail. It says, “Customer service has evolved in the past several years, as savvier shoppers expect retailers to understand exactly what they need, when they need it. Big data analytics technology helps retailers meet those demands. Armed with endless amounts of data from customer loyalty programs, buying habits, and other sources, retailers not only have an in-depth understanding of their customers, they can also predict trends, recommend new products—and boost profitability.” The retail industry is an important part of the U.S. economy. The National Retail Federation reports, “Retail is the nation’s largest private-sector employer, contributing $5.3 trillion to annual GDP and supporting more than one in four U.S. jobs—55 million working Americans.”

Data Analytics Job Titles and Salaries

Data Analyst

A Data Analyst collects, processes, and analyzes data. When you first start out in this career, you may work as a Junior Data Analyst, and with more experience, you could work your way up to a Senior Data Analyst position, where you work with more complex sets of data. The World Data Science Initiative reports that there is a huge deficit of qualified professionals in the field of data analytics. It says, “Finding equipped talent in the data science domain is tough. People adept at understanding and using data to drive business benefits are a rare gem to find. The demand for data analysts and scientists is like gushing water that is unstoppable and the supply is like a trickle.” As a result, it argues, “If you are a millennial or a Generation Z professional, there can’t be a better opportunity in the present job market than starting a career in data science.” According to Payscale, a U.S. Data Analyst earns approximately $67,000 yearly.

Data Scientist

The job of a Data Scientist is similar to the job of a Data Analyst but is also distinct. In general, a Data Scientist has more education and experience than a Data Analyst and earns a higher salary. Further, Data Scientists analyze data, but they may also work on creating new methods of data analysis. According to the U.S. Bureau of Labor Statistics (BLS), between 2022 and 2032, data science jobs will grow by 35 percent. This is significantly faster than the average U.S. job growth rate of 3 percent. The BLS says, “Employment growth for data scientists is expected to stem from an increased demand for data-driven decisions. The volume of data available and the potential uses for that data will increase over the projections decade. As a result, organizations will likely need more data scientists to mine and analyze the large amounts of information and data collected.” It finds that California, New York, and Texas employ the most Data Scientists, and California, Washington, Virginia, and Delaware are the highest-paying states. Payscale reports that the average U.S. salary for a Data Scientist is $100,000.

Financial Analyst

A Financial Analyst analyzes financial data to help companies make better financial decisions. The BLS predicts that Financial Analyst jobs will increase by 8 percent over the next ten years. It explains that there are several factors for the projected growth. It says, “Emerging markets throughout the world are providing new investment opportunities, requiring expertise in geographic regions where those markets are located.” In addition, it says, “Demand also is projected to increase as big data and technological improvements allow Financial Analysts to conduct high-quality analysis.” New York, California, and Texas employ the most Financial and Investment Analysts, according to the BLS, and New York, Wyoming, and New Jersey pay the highest wages. Payscale reports that a Financial Analyst in the United States has an average salary of $67,000.

Machine Learning Engineer

The job of a Machine Learning Engineer is sometimes referred to as a combination of data science and software engineering. It involves using data to design computer learning models, which allow computers to take specific actions without being explicitly programmed to do so. According to a recent article posted on the Built In website, there is a very high demand for Machine Learning Engineers in the current job market, and that demand is increasing. The author says, “If you have been considering getting into machine learning, now is the time to start. Demand for Machine Learning Engineers (already in short supply) is high and only expected to grow as the complexity of, and access to, machine learning increase.” As reported by Payscale, a Machine Learning Engineer earns about $118,000 annually in the United States.

Data Analytics Classes Near Me

Many different schools offer data analytics classes in a live online format. Noble Desktop is located in New York City, where it runs in-person classes in addition to live online options. This school was founded in 1990 and is licensed by the New York State Education Department. Its Data Analytics Certificate is popular. This is a multi-week program designed to give you the skills you need to be a Data Analyst or Business Analyst. You’ll learn about data analysis, statistical analysis, and data visualization, working on several real-world projects. In addition, you’ll receive eight one-on-one mentoring sessions where you can get extra help with challenging concepts or get resume and portfolio advice. Noble Desktop classes also come with the option of a free retake within a year.

Another popular Noble option is the Data Analytics Technologies Bootcamp. This course is designed to help you master the different tools and programming languages used in the data analytics industry. You’ll learn to work with Excel, SQL, and Tableau, and practice your skills on real-world projects. You’ll organize, analyze, and summarize data, and present actionable insights. This is a multi-day course. No previous experience is required. At the end of the course, you’ll receive a certificate of completion.

If you’re looking for a shorter class, Noble runs a Data Analytics Foundations class, which is focused on fundamental data analysis skills. In this class, you learn about the data analytics process, which includes inferential statistics, descriptive statistics, and data distributions. You’ll also learn about how different industries and organizations apply data and what tools they use, as well as getting an understanding of the role Big Data plays in the business world. In addition, you’ll learn statistical analysis and modeling tools such as statistical algorithms, theorems, and models. If you want to take this class, you should be comfortable using Excel at a basic level.

Noble Desktop also offers several classes that focus on specific tools used in data analytics. Excel for Data Analytics is a short class focused on learning to use Excel for data analytics. You’ll learn essential functions and formulas for data analysis. You’ll also learn advanced techniques. Some of the specific skills covered include common database and statistical functions, sorting and filtering data, macro creation for data analytics workflow, Pivot Tables, and VLOOKUP. Instructors also cover tips and tricks to speed up your workflow.

Another school option is General Assembly, which was founded in 2011 and offers a variety of different tech bootcamps in more than 20 cities around the world, in addition to in a live online format. Its Data Analytics Bootcamp is a multi-week program where students learn a wide range of data analytics skills. The bootcamp covers acquiring and cleaning data, statistical and mathematical data analysis, and principles of responsible data analysis. Students also learn to use many different data analytics tools including Python, Power BI, Tableau, and Excel. Finally, they complete a capstone project. Tuition includes access to a personal career coach who can help students gain a better understanding of the job market.

If you want to learn Python for data analytics, NYIM Training offers a class called Python for Data Science Bootcamp. This is a multi-day class focused on data visualization and machine learning techniques. Students learn how to use Pandas and scikit-learn to input, analyze, and make visual representations of data. Specific skills covered include data types within Python, control flow, looping, functions, and object-oriented programming. Students also work on a special data science project. NYIM Training is a professional development school based in New York City that has been operating since 1998.

Another Python option is Python Programming for Data Analytics, offered by the New York City College of Technology, a school that was founded in 1947 and offers training programs for thousands of students. In this class, students learn about Python scripts, object-oriented programming, data acquisition, data wrangling, and data cleaning. Specific topics covered include data structures, lambda functions, list comprehension, decorators, generators, iterators, logging, and Python packaging. Students also receive coaching on how to pass a Python/Data Analyst interview.

If you want to learn to use Microsoft Power BI, you can take a class through ONLC Training Centers, which was founded in 1983 and offers computer training classes live online and at hundreds of training centers across the United States. Microsoft Power BI Analyst is a multi-day class where students learn about modeling, visualizing, and analyzing data with Power BI. They will learn to clean, transform, and load data in Power BI, design a data model, create model calculations, and optimize model performance. They will also learn to create reports and dashboards and enhance reports for usability. In addition, the class covers advanced analytics, managing datasets, and creating and managing workspaces.

The Digital Workshop Center also offers online data analysis training. The Data Science Certificate Program is a multi-week course. Students cover a wide range of different data science skills including working with R software, organizing and cleaning data, descriptive statistics, plotting data and writing functions, using a basic linear regression model, and using predictive statistics. They also learn to automate repetitive tasks, create automated reports, and problem-solve with programming. In addition, instructors cover the basics of optimization and the basics of machine learning. Students also receive career coaching and one-on-one mentoring. To take this class, students should have intermediate knowledge of Excel and a basic knowledge of programming concepts. Experience with applications of programming in a business environment is recommended but not required.

The American Management Association is an organization that works to promote management. It runs a class called Data Analysis Fundamentals: A Hands-On Workshop, which is designed to give students tools with which to make better business decisions. Students who take this class learn about using the Data as Strategic Model tool, framing the right questions to get the best results, and collecting and organizing data in the right way. They also learn to identify the relevance of data, interpret and translate it into actionable insights, and apply analytical tools to business questions.

This school also offers a class called Advanced Tools and Techniques for Data Analysis. This short class is designed for business professionals who want to learn to use data analysis techniques. No experience in statistics or programming is required. Students learn about wrangling, cleansing, and shaping data, using Google OpenRefine, and selecting the right variables for data analysis. They will also become familiar with Excel’s Analysis ToolPak. The class also covers multivariate statistics, T-Test, factor analysis, linear regression, and other advanced techniques. In addition, students learn to use JMP, Tableau, SPSS, and R.

The Borough of Manhattan Community College offers a live online data analysis class called Python Data Analysis, where students can learn to analyze data using Python. This is not a beginner class; students should already have some knowledge of Python. The class covers preparing data for analysis, performing simple statistical analysis, creating data visualizations, and predicting future trends from data. The Borough of Manhattan Community College is a community college in New York City that was founded in 1963.

Data Analytics Corporate Training

Data analytics skills are a valuable asset to almost any business. For companies interested in providing a group of employees with data analytics training, Noble Desktop offers onsite and virtual corporate data analytics training. All of Noble’s classes are conducted by experienced instructors who also have extensive industry experience. Instructors can conduct onsite training at your business or run a class live online through Zoom or a similar platform. Course content can be customized and includes support materials like handouts and training videos for students to access after the training is complete.

If your employees would prefer a more flexible training option, you can buy them vouchers for Noble Desktop’s regular group data analytics classes and let them enroll individually. With this option, employees can choose their own schedules. There is a discount with bulk voucher purchases. Contact Noble Desktop for more information about corporate training options.

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Upskill or reskill your workforce with our industry-leading corporate and onsite Data Analytics training programs. Conduct the training onsite at your location or live online from anywhere. You can also purchase vouchers for our public enrollment Data Analytics courses.

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Data Analytics Certificate Learn The Skills Guarantee™

Key Insights

Learn More About Live Online Data Analytics Courses

What Can You Do with Data Analytics Training?

What Will I Learn in a Data Analytics Class?

Gathering Data

Using Programming Languages

Statistical Analysis

Analytics Platforms

Communication Skills

Communication Skills

How Hard is It to Learn Data Analytics?

What Are the Most Challenging Parts of Learning Data Analytics?

How Long Does It Take to Learn Data Analytics?

Should I Learn Data Analytics in Person or Online?

Can I Learn Data Analytics Free Online?

What Should I Learn Alongside Data Analytics?

Industries That Use Data Analytics

Finance

Tech

Public Sector Industries

Retail

Data Analytics Job Titles and Salaries

Data Analyst

Data Scientist

Financial Analyst

Machine Learning Engineer

Data Analytics Classes Near Me

Data Analytics Corporate Training

Live Online Data Analytics Corporate & Onsite Training Noble Desktop

Related Classes

Live Online Data Analytics
Corporate & Onsite Training