Introduction to Hypothesis Testing Typically in the field of hypothesis testing, that will also involve thinking up and developing critical tools for any data professional interested in determining the statistical significance of hypotheses or experiments with respect to random chance. This is actually a complete guide to all steps involving a hypothesis test for an … Read more
INTRODUCTION – Confidence Intervals For the rest of the section, students will engage with the fundamental, but complicated, idea of the confidence interval. Students will also explore how data professionals use confidence intervals to indicate the uncertainty that accompanies an estimate. The student learns how to build confidence intervals, develop interpretations, and understand the potential … Read more
INTRODUCTION – Sampling Participants will learn the exact model where small samples are used to reach intelligent conclusions about larger data-gathering-a fundamental effective data analysis model. Following an exposition on methods used by data professionals for collecting and analyzing sample data, the module focuses on avoiding any instance of sampling bias to maintain integrity and … Read more
Introduction to Statistics It is currently your data set of training until October 2023: A full-fledged module that guides participants through the complex world of probability by starting from a very solid foundation on single-event probability basic rules. The following modules will be set for more complex events and will teach advanced methods like Bayes’ … Read more
INTRODUCTION – Data Visualizations and Presentations It is exactly to train you to even improve this efficacy with your stories such that they are ethical, accessible, and definitely professional. Follow advanced data visualization practices through Tableau to create compelling and impact visuals. Besides, talk about responsible data presentation, including ethics and transparency, and also cover … Read more
Module 2: Explore Raw Data INTRODUCTION – Explore Raw Data In EDA or Exploratory Data Analysis, we organize and analyze raw data to bring out insight from it. This is a complete role of Python, which enables you to easily and quickly perform huge data discovery patterns. Sculpting for further analysis to decipher the insight … Read more
INTRODUCTION – Find and Share Stories Using Data Learn the skill of makings sense out of data in sexy storylines and communicating them to your audience. The importance of data cleaning the most crucial process to reveal relevant information lies in this chapter. Explain the phases of Exploratory Data Analysis, which include the power of … Read more
Module 4: Data Applications And Workflow INTRODUCTION – Data Applications And Workflow In this course, you’ll learn the PACE project workflow (plan, analyze, construct, and execute)a project and how to effectively organize a data project. You will learn how to effectively communicate with your teammates and stakeholders. Learning Objectives: Apply communication principles to real-world data … Read more
Module 1: Introduction to data science concepts Introduction to data science concepts An introduction to beginning the Google advanced data analytics certification: main objectives and components. History of data science: the subject will be used effectively to discuss modern-day problems. Objectives for Learning Having clear ideas about the programme structure and expectations. Explore the nature … Read more
Module 2: Functions and Conditional Statements INTRODUCTION – Functions and Conditional Statements This section will help you to work with functions to carry out various useful activities on data. It will also tutor you on writing conditional statements that will let a program take action when given particular specifiedted commands. Practice also writing code that … Read more