Enhance your analytical thinking through lessons in Excel, SQL, and Tableau. Learn to use data visualization to guide strategy and innovation.
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.
Data analytics is the process of analyzing raw data to find trends and answer questions. Applicable in any industry, this process includes extensive sets of diverse data—structured, unstructured, and semi-structured—that are continuously generated at high speed and in high volumes.
Big data is typically measured in terabytes or petabytes, with one petabyte equal to 1,000,000 gigabytes. One petabyte is the equivalent of 250,000 films, and the large datasets used in data analytics measure anywhere from hundreds to thousands to millions of petabytes. (That’s a lot of data!)
A successful data analytics professional can help answer business questions related to historical trends, future predictions, and decision-making. Machine learning tools, massive datasets, and more affordable computing power have made these techniques applicable in many industries, helping businesses draw meaningful conclusions from complex and varied data sources.
If you speak with a Data Scientist or analyst, they’ll tell you that it’s more than just a potential profession. Data analytics is a hobby, a passion, one that can be applied in all areas of life. Noticing issues in your neighborhood? You could use urban data flows to predict and prevent infrastructural issues like potholes through a complex analysis of factors like traffic volume, pavement age, weather, and traffic accidents. Whether you’re on your local HOA board or presenting to your city council, your insights can help better your community.
Or, you could use predictive analysis to gather information on various sports-related topics, allowing you to make strategic choices in your fantasy leagues based on current team and player strengths and weaknesses.
Data analytics is, at its base, the combination of noticing patterns and a healthy amount of math and statistics. These things exist in everything around you, so data analytics can apply to almost anything you can think of.
Data analytics courses can teach you about the data analytics process (including collecting, wrangling, mining, and visualizing data), different data roles, and data structures. Basic math and data skills, like probability, statistics, and theoretical concepts, will be covered as well. For technical skills, you can expect to study programming languages like Python, database tools like Excel, and data visualization tools like Tableau.
You’ll most likely also learn how to apply analytical techniques and tools in various contexts through projects that simulate real-world data challenges. These projects enhance your learning and help build a portfolio that you can use when applying for jobs. By the end of a data analytics course, you should be competent and confident enough to begin or expand a career in data science and analytics.
Given the field’s complexity and the diverse skill set required to excel, data analytics is considered somewhat challenging to learn, blending elements of statistics, mathematics, computer science, and specific industry knowledge. In data analytics, both the initial learning curve and the requirement for continuous learning are substantial, largely because of the breadth of the field and the continual advancement of technology. While data analytics comes with its challenges, it is ultimately a field that anyone can master. With the right amount of passion, dedication, and time, anyone can become an expert in data analytics.
Data analytics is a broad field; the time it takes to learn depends on several factors. You can master the basics of data analytics in less than a year, but your level of expertise will include various skills and practice in a particular role. You shouldn’t expect to become an advanced data pro in a matter of months.
The time required also depends on your existing knowledge and how much time you can dedicate each week. With full-time dedication (30-40 hours per week), you can become proficient in around three months, while part-time learners (15-20 hours per week) might take six months or more.
One factor to consider is the type of training you choose. Self-guided data analytics education can take much longer than a targeted bootcamp or certificate, so choosing the right course that fits your schedule is paramount to your success and efficiency.
There are several other skills that you can start working on while studying data analytics. While you’ll most likely have the experience needed in mathematics and statistics, it can’t hurt to brush up on those two subjects. Additionally, programming languages like Python, R, Java, C, or Perl will be very useful.
Hadoop is one of the most popular Big Data frameworks. Most professional arenas will expect (or hope) that you have experience in Hadoop, so it can’t hurt to tackle it alongside data analytics. Likewise, SQL is the most common way of getting information from a database and updating it, so if you can master SQL as well, you’ll be a step ahead of your career competition.
Technology is perhaps the most well-known industry in San Francisco, thanks to its location just 40 miles north of Silicon Valley cities like Cupertino, Palo Alto, and Mountain View. The Bay Area is also home to several tech giants like Salesforce, Instacart, Apple, and Lyft, and is a prime location for start-ups. The region employs more than 400,000 tech professionals, and you could be one of them.
Social and digital media is another thriving industry, consisting of more than 300 digital media companies like YouTube, Electronic Arts, Zynga, X (formerly known as Twitter), Dolby Laboratories, Pixar, Sony, Sega of America, Konami Digital Entertainment America, and PDI DreamWorks SKG. YouTube alone contributed $35 billion to the U.S. gross domestic product and supported over 390,000 full-time equivalent jobs in 2022, so it isn’t hard to see the success and growth of this industry in San Francisco and beyond.
Serving as an international center for trade, San Francisco has long been the gateway between America and the Pacific. It is the largest U.S. exporting region to Asia, with more than 71 consulates and foreign trade offices located in the city. It is also the tenth largest exporting region in the U.S. and the financial services epicenter of the West Coast housing 30 of the largest non-American banking institutions in the country like Barclays Bank of the United Kingdom, Sumitomo Bank of Japan, Banco di Roma of Italy, Banque Nationale de Paris of France, Hong Kong and Shanghai Bank of China, Industrial and Commercial Bank of China, HSBC, Lippo Bank of Indonesia and The Royal Bank of Scotland.
Regardless of the industry you choose to pursue, each field will need highly skilled data analytics experts to help guide their decision-making. Below are some of the top job titles you may see across various industries to help you pinpoint your exact career path.
There are several exciting career options available for both those who are just getting started in the field of data analytics and those looking for advancement. Each position will have a unique specialty or focus, so you’ll want to have a clear understanding of how you’d like to apply your data skills professionally.
Financial Analysts guide individual stakeholders, businesses, and companies on how best to invest money and resources to gain the maximum profit. They will analyze multiple factors like business environments, market trends, financial status of companies, expected outcomes of operations, and past financial data to make the most informed and calculated decision. According to the U.S. Bureau of Labor Statistics, Financial Analysts make a median salary of $100,000 per year. In San Francisco, the expected salary range is anywhere from $108,000 to $130,000.
Database Developers study database processes, intending to update them, improve their efficiency, and getting rid of inefficient coding. They keep track of how existing databases are performing and use code and web architecture to create data systems, analyze and maintain existing databases, and implement new user features. The U.S. average is around $117,000 for a Database Developer, Administrator, or Architect, but in the San Francisco area, the median base pay is closer to $143,000.
Do you also have an interest in meteorology? Weather Analysts study atmospheric occurrences and analyze data about meteorological events to provide forecasts and reports. It’s important they have a sound understanding of math and statistics and are also familiar with meteorology. Meteorologists and Atmospheric Scientists across the country make around $92,000 per year, so you can expect to make near that as a Weather Analyst, with many Bay Area professionals earning closer to $104,000.
Offered by Noble Desktop, the in-depth Data Science & AI Certificate can take anywhere from four to 20 weeks to complete. You’ll learn all the skills needed to become a professional Data Scientist, like how to manipulate databases and perform data analysis, master the fundamentals of Python programming, and use its main data science libraries to analyze data. You’ll also try your hand at creating machine learning models, making dashboards and visualizations, and deploying your projects online with GitHub. Held live online, this course includes access to 1:1 mentoring, a free retake within one year, and a verified digital certificate upon completion. Small class sizes and live project-based training with industry experts help ensure you gain all the knowledge and experience needed to land your dream Data Scientist job.
The Data Analytics Certificate is a project-based course from Noble Desktop that teaches you to gather, wrangle, analyze, and visualize data using various tools and technologies to help businesses in decision-making and strategy. You’ll work on multiple real-world projects to explore both predictive and prescriptive analytics and gain practical experience. Plus, you have access to 1:1 mentoring, a free retake, and setup assistance when you enroll in this course. Payment plans are available to make this certification more accessible.
There are also several bootcamps and short courses that get you prepped for a career in data analytics, such as the Python for Data Science Bootcamp, the Data Analytics Technologies Bootcamp, and Excel for Data Analysis. You have so many options at Noble Desktop, which makes it easier than ever to build your skills and prep for the real-world data analytics career path.
Want to offer in-person or online training to your office or team? Noble Desktop can help. They offer a variety of corporate training programs, including in Premiere Pro. You can order vouchers in bulk at a discount, choose which courses are available to employees, and even let your employees choose their own schedule. Plus, you can choose to have your training hosted at a location of your choosing, live online, or at Noble Desktop’s Manhattan office.
With a top-notch customizable curriculum and instructors who are experts in their industries, Noble Desktop’s corporate training caters to your business or organization’s needs. For more information or to schedule a free consultation, you can reach out to Noble Desktop at corporate@nobledesktop.com.
If you’re searching for professional opportunities in fields related to tech, design, business, and data, look no further than San Francisco. The city is a global hub for innovative technologies, startups, and financial institutions, with some big-name companies like Google and Wells Fargo calling the Bay Area home. With proper training in data analytics, you can find work in any of the major San Francisco companies. It's one way to make smarter decisions through actionable insights, giving you a skillset that's in high demand across industries. Through Noble Desktop’s quality instructors, you’ll be able to start your career in one of these fields quicker than you think. Their combined decades of experience give professionals and aspiring experts the skills that they’ll need to excel in a real-world setting without having to sacrifice hands-on learning. It’s an ideal place to find training that teaches technical skills and practical applications to serve you well in the job search and beyond.
As an experienced educator, researcher, and conference speaker, Dr. Deanne Larson brings her industry experience to the classroom, often teaching classes related to data, AI, Python, and project management. Her professional career is exceptional, beginning with her earning three doctorates in Computer Science (AI), International Management, and Management, as well as a Master’s in Business Analytics. Beyond academia. Dr. Larson has also worked in the field of data science and analytics for over 20 years, serving as an advisor to Fortune 500 companies, global enterprises, and FinTech startups through her firm, Larson & Associates, LLC. Her work spans AI-driven strategies, fraud detection machine learning models, and data governance solutions in cloud and blockchain environments. Her extensive training and career accomplishments give her the credibility to impart her knowledge to her students.