Data Analytics Certification Training in Portland, ME

The course syllabus is specifically designed to help learners acquire skills for setting achievable goals in the business field. Data analytics is the collection, transformation, and organization of data in order to draw conclusions, make predictions, and drive informed decision-making. Data analysis is a process for obtaining raw data and subsequently converting it into something useful for users’ decision-making. It is a process of inspecting, cleansing, transforming, and modelling data to discover useful information, inform conclusions, and assist decision-making. The Data Analyst certification course will equip you with the latest analytics tools and techniques, how to work with SQL databases and basic SQL queries, the programming languages of R and Python, raw data manipulation, the art of creating data visualizations, and how to apply statistics and predictive analytics in a business environment. Steps in data analysis? To improve your data analysis skills and simplify your decisions, execute these five steps in your data analysis process: • Define Your Questions • Set Clear Measurement Priorities • Collect Data • Analyze Data • Interpret Results Key Features: • 3 Days of Classroom Setting/Online Instructor-Led Live Training • 24 PDUs Offered • Experiential Learning with Case studies and Simulations • Get Trained by a Globally Renowned Certified Data Analytics Instructor • 24/7 Customer Support What you'll learn: • Gain an immersive understanding of the practices and processes used by a junior or associate data analyst in their day-to-day job • Learn key analytical skills (data cleaning, analysis, & visualization) and tools (spreadsheets, SQL, R programming, Tableau) • Understand how to clean and organize data for analysis and complete analysis and calculations using spreadsheets, SQL, and R programming • Learn how to visualize and present data findings in dashboards, presentations, and commonly used visualization platforms Skills you’ll gain will include: Data cleaning, problem solving, critical thinking, data ethics, and data visualization Data Fundamentals: • Course Overview and Level Set • Understanding Real-World Data • Types of Data • LAB: Hands-on – Profiling Data • Data-related Risk • Data Quality • LAB: Hands-on – Dealing with Duplicates • Relationships • LAB: Hands-On – Data Relationships using PowerPivot Analysis Foundations: • Statistical Practices: Overview • Domains of Data • Analysis Analyzing Data • Statistical Practices: Overview • Averages in Data • Central Tendency • LAB: Hands-On – Central Tendency • LAB: Hands-On Linear Regression • Distributions • Correlation • LAB: Hands-On – Distributions in Consumer Finance Data • Analytical Graphics for Data • Analytics & Modelling • ROI & Financial Decisions • LAB: Hands-On – Helpful Financial Metrics in Excel • Using Financial Data • Random Numbers • Demo / Lab – Monte Carlo Analysis in Excel • Predictive Analytics Demo / Lab – Using R for Powerful Analysis • Clustering • Data Modelling • Data Warehousing • Visualizing & Presenting Data • Goals of Visualization • Visualization Essentials • Demo / Lab – Improving a Difficult Report • Communicating Data-Driven Knowledge Why global corporates prefer Learning Zone Inc. as a training partner An Enterprise Learning Solutions (ELS) provider, Learning Zone Inc. creates industry-fit talents through training, coaching, and consulting by globally acclaimed trainers. Much of Learning Zone’s repute in co-creating business value stems from: • Training delivered in 45+ countries. • 250+ industry-relevant courses. • Consulting and coaching to transform organizations. • Best value for time & money invested. • Trainers with experience in Retail, E-commerce, Energy & Utilities, etc. • Get trained at the best fee compared to other vendors • Discounted fee offered for 5 or more attendees *We provide corporate training at your preferred location and dates at no additional charge. Contact us for more information: Name: Debbie Riel Email: [email protected] Phone: +1 302.251.9769