Unlock the power of Python for data-driven decision-making as you master Python programming fundamentals and dive into data analysis. Acquire essential skills to clean and manipulate data, create insightful visualizations, and perform statistical analysis, all through hands-on projects with real-world datasets.
Learn to extract information from databases by writing SQL queries, joining tables, aggregating data, and filtering results. You'll learn PostgreSQL in this class, but the concepts apply equally to other databases such as SQL Server and MySQL.
Become proficient in Microsoft Excel and go from beginner to pro with our hands-on Excel Bootcamp. Learn functions, formulas, Pivot Tables, macros, and time-saving techniques to conquer all the key skills needed to excel in Excel.
Learn how to use Tableau, a powerful data visualization tool, to create interactive and aesthetically pleasing charts, graphs, and maps. This course will teach you how to connect to datasets, analyze and structure data, customize visualizations, and publish your work.
Learn how to use Power BI, a powerful data visualization tool, to create interactive and aesthetically pleasing charts, graphs, and maps. Learn how to connect to datasets, analyze and structure data, customize visualizations, and publish reports.
Learn the fundamentals of data analytics, including descriptive and inferential statistics, and how different industries and organizations use data for forecasting and decision-making. Explore statistical analysis and modeling, including statistical algorithms, theorems, and models.
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.
Automate and enhance the data analysis process with artificial intelligence (AI). In this course, you'll learn how to utilize AI tools to collect, preprocess, analyze, visualize, and interpret data without the need for extensive coding knowledge.
Learn to gather, manipulate, and analyze real-life data in this course, where you'll gain hands-on experience with Python's NumPy and Pandas libraries. Develop your data visualization skills using Matplotlib, Seaborn, Plotly, and Dash Enterprise, and complete real-life projects that can be deployed online.
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 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 Tableau for data visualization and become a certified Tableau Desktop Specialist in this hands-on certification course.
Learn to extract information from databases by writing SQL queries, joining tables, aggregating data, and filtering results. You'll learn PostgreSQL in this class, but the concepts apply equally to other databases such as SQL Server and MySQL.
Learn Power BI for data analysis & visualization and become a certified Power BI Data Analyst Associate in this hands-on certification course.
Boost your resume with a Microsoft Excel Certification. Our program offers three courses, private training, the Specialist Exam fee with free retake, lifetime access to Excel video courses, and free exam proctoring.
The analytics side of data science requires analysis and interpretation of large datasets. Data Analysts offer actionable insights based on their analysis that can help organizational leaders make data-driven decisions. While Data Scientists typically extract and prepare data, Data Analysts provide conclusions.
Analytics pros can hold numerous titles, including:
Although the history of information storage and analysis goes back thousands of years, modern data analytics is a relatively new phenomenon. Data analysis using AI has advanced rapidly in the 21st century, and the field continues to expand. Read on to learn more about data analytics.
Data analytics applications include everything from writing SQL queries to creating insightful data visualizations. Data Analysts, Business Intelligence Analysts, and Financial Analysts harness the power of frameworks and libraries to manage and analyze massive datasets. Consider the following data analytics projects:
The skills and tools you learn in a data analytics class depend on several factors. First, you might learn Python through a broad data science curriculum. In cases like this, you will most likely master multiple Python libraries as part of your training.
Top Python libraries include:
However, you might take a shorter seminar or workshop, where you may only get a few data analytics fundamentals. For example, you might enroll in a class focused on SQL, Tableau, or Power BI. Alternatively, you might find a happy medium between beginner-level coursework and immersive training.
Python is essential for Data Scientists, Data Analysts, AI Engineers, and many other data professionals. Most data analytics courses cover beginner-level, intermediate, or advanced Python for data science, automation, AI, or all three. If you don’t master Python in your initial data analytics training, you’ll likely need to learn it later.
Many tech professionals use SQL to store, query, and process data—from Data Scientists and Data Analysts to Web Designers and Full Stack Developers. A broad data science or analytics curriculum typically features SQL Server or MySQL.
Data visualization is another essential skill most data analytics and data science curricula provide. Among the most popular business intelligence tools for data visualization are Microsoft Power BI and Tableau. While some companies prefer one over the other, many organizations prefer job candidates who have some familiarity with both.
A class will help develop your critical thinking skills, which you’ll need it for most tech roles. Critical thinking, logic, problem-solving skills, and attention to detail are all essentials for Data Analysts and other data-centered roles.
The hardest part of learning data analytics depends on the student and their current skills and aptitude. Those who know Python, SQL, or even Microsoft Excel approach data analytics training with relevant skills. However, using these skills in analytics can differ from using them for development or automation. Students planning to launch careers in data, business, or financial analysis benefit from bootcamps or certificate programs that feature analytics or include it within a broader data science curriculum.
The most challenging part of learning data analytics can be figuring out how to integrate new and existing skills. Some courses teach a programming language like Python, a skill like SQL, and a data visualization tool like Tableau. Putting all the pieces together in a portfolio project can help data analytics novices combine these disparate tools and skills.
Getting comfortable experimenting with data analytics is a great start, but learning fundamentals is different from becoming an expert. Training to be a Data Analyst can take months or even years. However, an in-depth bootcamp or certificate program from a respected course provider can help novices qualify for an entry-level data analytics role.
One of the first decisions you must make when choosing data analytics training is the type of class you will take. Factors influencing your decision include budgeting, scheduling, and personal learning style. Consider the three most common types of training programs:
In-person training offers unique advantages. Learning in the traditional classroom setting gives students the highest possible level of engagement. They can interact with their instructor and classmates, and many report feeling more connected to the material in a classroom.
However, learning live online has become more popular than ever. Online learning provides engagement comparable to in-person training, and many course providers offer a virtual option. Another advantage of training live online is that it increases the number of training options. You can take live online classes anywhere with a reliable internet connection.
On-demand learning also has unique advantages and drawbacks. This method typically includes recorded videos, though some courses include supplementary materials like workbooks. Asynchronous training may appeal to you if you have a non-traditional work schedule, like the second or third shift. You can pause videos whenever you want, and many on-demand programs are less expensive than traditional alternatives.
The biggest drawback of on-demand training is its lower level of engagement. Some students feel unmotivated when training by prerecorded video, and the lack of feedback from instructors or peers can be a downside. Consider rearranging your schedule, if possible, to attend live classes for data analytics training.
As in any business or computer science career, what you learn alongside data analytics depends on the position you want, your current skills and experience, and what resources are available to you. For example, the Data Analytics Certificate from Noble Desktop combines Excel, Python, SQL, and Tableau, all appropriate for an entry-level Data Analyst position. However, if you want to learn data analytics for AI, your best option might be the Data Science & AI Certificate program.
Large organizations make data-driven decisions, so they need Data Analysts, Business Analysts, or Financial Analysts. Data analytics jobs in Houston include healthcare, aerospace, technology, and the energy industry. Salaries in Houston can run above national averages, and the city has a lower-than-average cost of living and is the most populous city in Texas. Consider the following industries when looking for data analytics positions in the Houston area.
With top organizations like NASA’s Johnson Space Center and Houston Spaceport, Houston is known worldwide for space exploration. The region employs thousands of aviation and aerospace pros, including Data Analysts and Safety Analysts.
Digital technology includes software and hardware companies, and these need data analysis for planning and marketing. Top digital technology products include batteries, sensors, and wireless devices, to name a few. Consider tech subcategories like cybersecurity, logistics, and robotics when looking for digital tech jobs in Houston.
Houston is the Energy Capital of the World, with over 250,000 employees in the metro area. Data Analysts, Business Analysts, and Energy Risk Analysts are among the many analytics roles available here. Consider oil, gas, solar, and wind-related companies like ExxonMobil, Shell, and NRG Energy when seeking data analysis roles in Houston.
Unlike the digital technology sector, biotechnology and life sciences include everything from pharmaceuticals to biology. Top Houston organizations that employ the 400,000+ workers in this industry include Rice University and the University of Houston. Look for quality assurance, R\&D, and business intelligence analysis roles here.
With an average salary higher than national averages, Houston attracts data analytics professionals from around the country. Check out the following titles and their average annual compensation in this affordable and dynamic metro area.
Today’s Business Intelligence Analysts work in nearly every industry and sector, from medical practices to marketing companies. In Houston, a BI Analyst can expect to earn an average annual salary of about $59,000, not including 401(k) plans, bonuses, or other compensation.
Data Analysts sometimes move up to Data Scientist roles, but others prefer to stay in analysis. Houston-area Data Analysts work in industries ranging from manufacturing to retail and can anticipate earning an average annual salary of around $77,000, depending on experience.
Data Scientists often start as BI Analysts, Data Analysts, or even Software Developers. These skilled pros are among the most respected computer science workers and frequently earn over six figures. Houston Data Scientists can anticipate an average annual salary of about $125,000, not including profit sharing, 401(k), or other compensation.
Financial Analysts work in industries as diverse as BFSI (banking, financial services, and insurance), energy, and healthcare. In Houston, the average annual salary for a Financial Analyst is around $83,000, which aligns with the national average for comparable roles.
Data Science & AI Certificate
Noble Desktop’s Data Science & AI Certificate provides hands-on training in Python, SQL, automation, and machine learning, making it ideal for beginners seeking entry-level roles in data science or Python engineering. The program covers programming fundamentals, data analysis, predictive modeling, and machine learning, complemented by real-world, industry-aligned projects. Students also receive one-on-one mentoring and a free Python for AI course to further prepare for the job market.
Classes are available in New York City or live online, with flexible scheduling. The 114-hour curriculum includes essential tools such as Pandas and scikit-learn, and graduates earn a verified New York State–licensed certificate. This program equips students with the skills needed to pursue high-paying opportunities in the rapidly growing field of data science.
Data Science Certificate
Designed for beginners eager to enter the in-demand field of data science, Noble Desktop’s Data Science Certificate covers Python programming, SQL querying, and machine learning. Students learn to analyze data, build predictive models, and create interactive dashboards while completing real-world projects to enhance their portfolios.
The program also provides personalized support for job searching, resume writing, and portfolio development through one-on-one mentoring with experienced data scientists. Courses are offered online with live instructors or in-person in New York City, making them accessible nationwide.
Python for Data Science Masterclass
In the Python for Data Science Masterclass, students gain hands-on experience with beginner and advanced Python programming tailored to data science. Over 60 hours, participants master data types, control flow, and functions, while working with libraries like NumPy and Pandas. The course also covers data analysis, visualization with Matplotlib and Seaborn, and advanced topics such as web scraping and API usage.
Classes are available live online or in New York City, with small group instruction, a verified certificate of completion, and a free retake within one year. Flexible payment plans are available, and students finish the course ready to tackle complex data science challenges.
Python for Data Science Immersive
This beginner-friendly program from Practical Programming focuses on practical skills in programming, data analysis, and visualization, preparing students for entry-level data science roles. Across five sessions, students learn foundational programming concepts, use Python libraries like NumPy and Pandas, create visualizations with Matplotlib, and apply linear regression using scikit-learn.
Emphasizing real-world applications, the course offers optional enrollment rewards and is available both live online and in-person in New York City, providing flexible access for learners.
Would your employees benefit from expanding their data analytics knowledge base? If so, consider corporate data analytics training from Noble Desktop. Corporate and onsite training is available live online via teleconferencing, and expert Noble Desktop instructors can even conduct training at your location.
Want your team to have more flexibility with their data analytics training? Noble offers discounted vouchers for its open-enrollment courses. Employers get a discount when they purchase the vouchers in bulk, providing a convenient option so an organization can select the training format that best suits its needs. Subjects include Excel, SQL, Tableau, Power BI, and more.
Want to learn more about the different data analytics training alternatives Noble Desktop can provide for your team? Contact Noble today for additional information and a free consultation.