Certification in Behavioral Analytics

Description

Take the next step in your career as behavioral analytics and storytelling professionals! Whether you’re an up-and-coming behavioral analytics specialist, an experienced data analyst focusing on behavioral insights, an aspiring data scientist specializing in behavioral data analysis, or a budding storyteller in data-driven narratives, this course is an opportunity to sharpen your data processing and storytelling capabilities specific to behavioral insights, increase your efficiency for professional growth, and make a positive and lasting impact in the field of behavioral analytics and storytelling.

With this course as your guide, you learn how to:

● All the fundamental functions and skills required for behavioral analytics .

● Transform knowledge of behavioral analytics applications and techniques, data representation and feature engineering for behavioral data, data analysis and preprocessing methods tailored to behavioral insights, and techniques specific to behavioral data narratives.

● Get access to recommended templates and formats for details related to behavioral analytics techniques.

● Learn from informative case studies, gaining insights into behavioral analytics and storytelling techniques for various scenarios. Understand how behavioral insights impact advancements in data visualization, with practical forms and frameworks.

● Learn from informative case studies, gaining insights into behavioral analytics and storytelling techniques for various scenarios. Understand how behavioral insights impact advancements in data visualization, with practical formats and frameworks.

The Frameworks of the Course

Engaging video lectures, case studies, assessments, downloadable resources, and interactive exercises. This course is designed to explore the field of behavioral analytics, covering various chapters and units. You'll delve into data representation and feature engineering for behavioral data, behavioral visualization techniques, interactive dashboards and visual analytics tailored to behavioral insights, data preprocessing, behavioral data analysis, dashboard design for behavioral analytics, advanced topics in behavioral data visualization, and future trends.

The socio-cultural environment module using behavioral analytics techniques delves into sentiment analysis and opinion mining, data-driven analysis, and interactive visualization in the context of India's socio-cultural landscape. It also applies behavioral analytics to explore data preprocessing and analysis, interactive dashboards, visual analytics, and advanced topics in behavioral analytics. You'll gain insight into data-driven analysis of sentiment and opinion mining, interactive visualization, and behavioral analytics-based insights into applications and future trends of data visualization, along with a capstone project in behavioral analytics.

The course includes multiple global data visualization projects, resources like formats, templates, worksheets, reading materials, quizzes, self-assessment, case studies, and assignments to nurture and upgrade your global data visualization knowledge in detail.

Course Content:

Part 1

Introduction and Study Plan

● Introduction and know your Instructor

● Study Plan and Structure of the Course

1. Introduction to Behavioral Analytics

1.1.1 Introduction to Behavioral Analytics

1.1.2 Key Components of Behavioral Analytics include

1.1.2 Continuation of Key Components of Behavioral Analytics include

2. Data Collection Methods

2.1.1 Data Collection Methods

2.1.1 Continuation of Data Collection Methods

2.1.1 Continuation of Data Collection Methods

3. Data Processing and Cleaning

3.1.1 Data Processing and Cleaning

3.1.1 Continuation of Data Processing and Cleaning

3.1.1 Continuation of Data Processing and Cleaning

3.1.1 Continuation of Data Processing and Cleaning

4. Descriptive Analytics

4.1.1 Descriptive Analytics

4.1.1 Continuation of Descriptive Analytics

4.1.1 Continuation of Descriptive Analytics

4.1.1 Continuation of Descriptive Analytics

4.1.1 Continuation of Descriptive Analytics

5. Predictive Analytics

5.1.1 Predictive Analytics

5.1.1 Continuation of Predictive Analytics

5.1.1 Continuation of Predictive Analytics

5.1.1 Continuation of Predictive Analytics

6. Behavioral Segmentation

6.1.1 Behavioral Segmentation

6.1.1 Continuation of Behavioral Segmentation

6.1.1 Continuation of Behavioral Segmentation

6.1.1 Continuation of Behavioral Segmentation

6.1.1 Continuation of Behavioral Analytics

7. A/B Testing and Experimentation

7.1.1 A B Testing and Experimentation

7.1.1 Continuation of A B Testing and Experimentation

7.1.1 Continuation of A B Testing and Experimentation

7.1.1 Continuation of A B Testing and Experimentation

8. Sentiment Analysis and Text Mining

8.1.1 Sentiment Analysis and Text Mining

8.1.1 Continuation of Sentiment Analysis and Text Mining

8.1.1 Continuation of Sentiment Analysis and Text Mining

8.11 Continuation of Sentiment Analysis and Text Mining

8.1.1 Continuation of Sentiment Analysis and Text Mining

9. Case Studies and Real-World Applications

9.1.1 Case Studies and Real World Applications

9.1.1 Continuation of Case Studies and Real World Applications

9.1.1 Continuation of case Studies and Real World Applications

9.1.1 Continuation of Case Studies and Real World Applications

10. Future Trends in Behavioral Analytics

10.1.1 Future Trends in Behavioral Analytics

10.1.1 Continuation of Future Trends in Behavioral Analytics

10.1.1 Continuation of Future Trends in Behavioral Analytics

10.1.2 Assessment

10.1.3 Understanding User Engagement on Social Media Platform

10.1.4 Methodology

10.1.5 Presentation of Findings

10.1.5 Continuation of Presentation of Findings

10.1.6 Prerequisites

10.1.7 Certification

Part 3

Assignments