### Introduction

A Certified Data Analyst (CDA™) successfully applies process of inspecting, cleansing, transforming and modeling data with the goal of discovering useful information, informing conclusions and supporting decision-making

**Program Rationale**

The role of a Certified Data Analyst is to apply the Data Management, Data Visualization, Data Statistics and Operational Analytics in their organization! Use of R-Studio Programming Language to handle big data and basic Tableau for Viz and create project in their organization using the tools that were acquired.

**Target Participants**

This program is suitable for professionals who want to further his knowledge, skills, and abilities on the utilization of Data Science methodologies, tools, and techniques covering problem definition, problem analysis, data modeling, insights generation, and data training.

**How to Get Certified**

Each candidate will be certified by **completing the training + e-learning, submitting the case study, successfully passing the exam and implementing an actual Data Analysis Capstone project**. This certification automatically includes a **FREE R – Studio Basic Level Certification upon completing its requirements**.

**Certified Data Analyst Program Outline**

**I. Phase 0: Introduction to Data Analysis**

**A. INTRODUCTION TO DATA SCIENCE**

1. Explain Business Decision and Analytics

2. List the types of business analytics

3. Discuss the application of business analytics

4. Describe data science

**B. ROLES OF DATA ANALYST IN INDUSTRY 4.0**

1. CDA Roles and Opportunities

**II. Phase 1: Data Management**

**A. Introduction to R programming**

1. Importance of R and significance to data analytics

2. Data types and variables in R

3. Types of R operators

4. Different types and conditional Statements in R

5. Different types of loops in R

6. Methods to Run an R script

7. Commonly used R functions

**B. Data Structure**

1. How to Identify data structures in R

2. Assign Values to data Structures

3. How to manipulate data using dplyr package

**III. Phase 2: Data Visualization**

**A. DATA VISUALIZATION** **USING R**

1. Describe Data visualization

2. List the graphics used for data visualization in R Explain ggplot with examples

3. Discuss file formats of graphic outputs

**B. DATA VISUALIZATION** **USING TABLEAU 10**

1. Describe the components and terminologies of Tableau Describe Desktop application, view, and data pages

2. Explain the fields generated by Tableau automatically

**IV. Phase 3: Data Statistics**

**A. DATA STATISTICS I**

1. Define Hypothesis

2. Explain Data Sampling

3. Confidence and Significance Levels

**B. DATA STATISTICS II**

1. Hypothesis Testing

2. Parametric Tests and Types

3. Non – Parametric Tests and Types

4. Hypothesis Tests on Population Means

5. Hypothesis Tests on Population Variance

6. Hypothesis Tests on Population Proportions

**V. Phase 4: Operational Analytics**

**A.REGRESSION ANALYSIS**

1. Explain the meaning and uses of regression analysis

2. Different Types of Regression Analysis Models

3. Functions to convert non-linear models to linear models

4. R –sq and adj R-sq Models

5. Principal Component Analysis and Factor Analysis of Dimensionality Reduction

**B. CLASSIFICATION**

1. Classification and the types of classifications algorithms

2. Logistic Regression

3. Support Vector Machines

4. K-Nearest Neighbors (KNN)

5. Naïve Bayes Classifier

6. Decision Tree and Random Forest Classification

7. Evaluation of classifier models

**C. CLUSTERING**

1. Define Clustering

2. List of Clustering Methods

3. Control charts

**D. ASSOCIATION**

1. Explain Association Rule

2. Apriori algorithm and application steps

**VI. Phase 5: Capstone Project**

**Program Feedback **

*“ lots of resources, both recorded videos and ebooks for self paced learning . Live classes were engaging and not boring and good course for starters, covered lots of topics and gained developing skill in short span of time”* – Angela Nebres

*“In this class, one of the most important lesson I’ve learned is the importance of accuracy of data and its structure to be able to manage it with good results.*“ – Khristelle Urgelles

### Join our program and get these perks!

✅ Lifetime Access to our eLMS

✅ 4 Live Classes + learning packages

✅ FREE R – Studio Programming Basic Course Certificate

✅ Per Module Certificate of Completion

✅ Certification Review & Examination

✅ Unlimited Project Coaching Hours

✅ Data Analyst Training Completion Certificate

✅ ALPHA Data Analyst Certification (TM)

✅ Almost 20 Million worth of Data to work during the course

✅ 30+hrs of Self Paced Lectures

✅ Limited Edition Reference Materials + Many more!

### Learning Investment

Regular Price: Php 80,000

Introductory Rate for the Self Paced Course: P9,990