Data Analytics

Data analytics is the process of examining and interpreting raw data to extract valuable insights, patterns, and trends. It involves using various statistical and computational techniques to make informed business decisions. By uncovering meaningful information, organizations can optimize strategies, improve efficiency, and gain a competitive edge.

Courses

• Introduction to Data Analytics (opens in a new tab): This course introduces the fundamentals of data analysis, exploring the role of a Data Analyst, tools utilized, data roles, structures, file formats, data sources, and the analysis process. It covers statistical analysis, analytical tools, techniques, and data visualization, offering practical skills for tasks like extraction, cleaning, manipulation, and analysis.

• Introduction to Statistics (opens in a new tab): Stanford University's course imparts a thorough grasp of statistical thinking, crucial for data comprehension and insight communication. It covers exploratory data analysis, sampling principles, significance tests, probability, central limit theorem, regression, and more. Designed to lay the groundwork for advanced studies in statistical thinking and machine learning.

• Data Visualization with Tableau Specialization (opens in a new tab): Geared towards Tableau beginners, this program teaches data visualization and storytelling through real-world examples. Utilizing Tableau's features, participants learn to create impactful reports and dashboards for informed decision-making. The specialization concludes with a Capstone Project, challenging participants to craft visualizations and dashboards for presentation to fictional executive leadership using sample data. The program is comprised of five courses: Fundamentals of Visualization with Tableau, Essential Design Principles for Tableau, Visual Analytics with Tableau, Creating Dashboards and Storytelling with Tableau and Data Visualization with Tableau Project.

• Google Data Analytics Professional Certificate (opens in a new tab) by Google, equips individuals with essential skills for a successful data analyst career. Comprising eight courses, it covers data collection, transformation, SQL, R programming, and tools like Tableau. Each course builds on prior skills, focusing on data cleaning, problem-solving, and visualization. The program is comprised of eight courses: Foundations: Data, Data, Everywhere, Ask Questions to Make Data-Driven Decisions, Prepare Data for Exploration, Process Data from Dirty to Clean, Analyze Data to Answer Questions, Share Data Through the Art of Visualization, Data Analysis with R Programming and Google Data Analytics Capstone: Complete a Case Study.

• Google Advanced Data Analytics Professional Certificate (opens in a new tab), tailored for those with prior experience or the Google Data Analytics cource, simulates real-world scenarios. Focused on workplace success, it covers advanced tools like SQL, R programming, Tableau, and Google Data Studio in a comprehensive curriculum for advanced data analytics proficiency. The program is comprised of seven courses: Foundations of Data Science, Get Started with Python, Go Beyond the Numbers: Translate Data into Insights, The Power of Statistics, Regression Analysis: Simplify Complex Data Relationships, The Nuts and Bolts of Machine Learning and Google Advanced Data Analytics Capstone.

• Mathematics for Machine Learning Specialization (opens in a new tab): By Imperial College London, bridges the gap between basic mathematics and its application in computer science, machine learning, and data science. Tailored for those refreshing their math knowledge for advanced machine learning and data science courses, it offers an intuitive understanding of relevant mathematics, providing a solid foundation for effective application of machine learning algorithms. The program is comprised of three courses: Linear Algebra, Multivariate Calculus and PCA.