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Data analysts shouldn't be confused with data scientists. Although both data analysts and data scientists work with data, what they do with that data, differs. A data analyst helps business leaders with decision-making by finding answers to a set of given questions using data. If you are interested in pursuing this career, these top 10 online big data analytics courses will be perfect for you.
Udacity's Data Analyst Nanodegree will teach you all of the knowledge, skills, and tools needed to build a career in big data analytics. In addition to covering both theory and practice, the program also includes regular 1-on-1 mentor calls, an active student community, and one-of-a-kind career support services. This program is best suited for students who have working experience with Python (and in particular NumPy and Pandas) and SQL programming. However, don't be discouraged if you lack these prerequisites. There's also a similarly structured beginner-level Nanodegree, "Programming for Data Science ", that is the perfect pick for you if you don't meet the prerequisites for this program. The beginner-level program covers just what you need: the basics of Python programming from a data science perspective.
Pluralsight's Big big data analytics with Tableau will not only give you a better understanding of big data but will also teach you how to access big data systems using Tableau Software. The course covers topics like big big data analytics and how to access and visualize big data with Tableau. The course is taught by Ben Sullins, who has 15 years of industry experience and has offered consulting services to companies like Facebook, LinkedIn, and Cisco. Sullins passes on his knowledge to students through bite-sized chunks of content. As such, students can personalize their learning to suit their individual requirements. You can finish the course in just a day or take your time and complete it over the course of a week or two. This course isn't necessarily for beginners. You're expected to have some experience with big data analytics. If you're a complete beginner, consider taking Data Analysis Fundamentals with Tableau, another course authored by Sullins.
Available on Udemy, Data Science Course 2022: Complete Data Science Bootcamp is a comprehensive data science course that consists of 471 lectures. The lectures include almost 30 hours of on-demand video, 90 articles, and 154 downloadable resources. While the course is not new and we first covered it back in 2020, it has been updated for 2022 with new learning materials. As part of this course, students can expect to learn in-demand data science skills, such as Python and its libraries (like Pandas, NumPy, Seaborn, and Matplotlib), machine learning, statistics, and Tableau. Although the course might seem a bit overwhelming at first glance, it's actually well-structured and requires no prior experience. All you need to get started is access to Microsoft Excel. The course will set you back a few hundred dollars. However, since Udemy runs generous discounts fairly regularly, you can get the course for under $20. Either way, this course is a steal, especially considering that you get full lifetime access to it and any future updates.
This particular path consists of seven courses: Learning big data analytics, Data Fluency: Exploring and Describing Data, Excel Statistics Essential Training: 1, Learning Excel: Data Analysis, Learning Data Visualization, Power BI Essential Training, and Tableau Essential Training (2020.1). Each course varies in length. However, most courses are between two and four hours long so that you can complete the entire path from start to finish in about 24 hours. There are no prerequisites to starting this learning path. Infact, you don't even need to know what data analysis is. The course begins by defining data analysis before teaching you how to identify, interpret, clean, and visualize data. The curriculum is taught via video by six different instructors, all of which are experts in the industry. Some courses include quizzes and every course has a Q&A section where you can ask the lecturer questions about the course. The only downside? There are no hands-on projects.
Designed by Springboard in partnership with Microsoft, big data analytics Bootcamp is a six-month career-focused program with a job guarantee. The Bootcamp goes over fundamental business statistics concepts and advanced analysis techniques and teaches students how to use analytics and visualization tools like Excel, Python, SQL, Tableau, and Microsoft Power BI. Throughout the course, students complete several small projects and two Capstone Projects sourced from Harvard Business School and Khan Academy. The entire course takes about 320 hours, or 6 months, to complete. Most students dedicate between 15 and 20 hours a week to the course. Each student also receives unlimited mentor calls and 50+ hours of career support.
This program features bite-sized learning materials curated by data industry experts. It will help you get your dream job in data analysis regardless of how much free time you have to study. DataCamp's Data Analyst with R Career Track consists of 19 data science analytics courses handpicked by industry experts to help you start a new career in data science. Since each course is about 4 hours long, the entire track should take about 77 hours to complete. At the end of this track, students should be able to manipulate and analyze data using R.
With a customized schedule, 1-on-1 mentorship, and 24/7 support from instructors, this course is as close to personalized learning as you can get. Thinkful's big data analytics Immersion is an intensive full-time training program. Although one of the more expensive big data analytics courses out there (it costs $12,250), it promises to take you from beginner to expert in just four months. However, students are expected to spend between 50 to 60 hours a week studying. Once you sign up for the course, you receive a customized schedule to help you stay on track. The curriculum consists of seven areas: Excel Foundations, Storytelling with Data, SQL Foundation, Tableau, Business Research, Python Foundations, and Capstone Phase. During the Capstone Phase, students not only get to build a final project but also complete two culture fit interviews.
Data Science Specialization offered by Coursera, together with the prestigious John Hopkins University, is a ten-course program that helps you understand the whole data science pipeline at a basic level. Although anyone can sign up for this course, students should have beginner-level experience in Python and some familiarity with regression. The curriculum is taught through videos and complementary readings. Student knowledge is tested via auto-graded practice quizzes and peer-graded assignments. The program culminates with a hands-on project that gives students a chance to create a usable data product.
This five-course series aims to teach students how to use big data to make data-driven business decisions in the areas of finance, human resources, marketing, and operations. Created by the Wharton School of the University of Pennsylvania and hosted on Coursera, the Business Analytics Specialization is divided into four discipline-specific courses (customer, operations, people, and accounting analytics). The final, fifth, course, is dedicated to a capstone project. The Specialization is taught through videos and readings. Your knowledge is tested via compulsory quizzes. You can also participate in discussion forums. At the end of the course, students complete a Capstone Project designed in conjunction with Yahoo. The entire Specialization takes about 40 hours to complete, which means that students can finish the program in just six months if they spend three hours a week learning.
Offered by Duke University and available on Coursera, the Excel to MySQL: Analytic Techniques for Business Specialization is a beginner-friendly course that teaches students how to obtain as much information as possible from the data they already have. The program is divided into five courses. You start off by learning best practices for using big data analytics to make a business more competitive before moving on to classes on Excel, Tableau, and MySQL. Each course ends with a project. For example, at the end of the third course, you have to give a five-minute presentation on how a business can increase the number of tests users complete. The final course is dedicated to the Capstone Project, which is sponsored by Airbnb. As part of this project, students have to make a recommendation on how a business can improve its profits. Every year, 10 students will get feedback on their projects from data scientists working at Airbnb.
