CDP Certified Data Developer Course Overview

CDP Certified Data Developer Course Overview

The CDP Certified Data Developer course is a comprehensive program designed to equip learners with the knowledge and skills necessary to become proficient data professionals. It covers a wide range of topics from the basics of data science to advanced analytics and cloud computing. The course is divided into twelve modules, each focusing on a critical aspect of data science and data engineering.

Starting with an introduction to data science, learners will explore concepts such as data collection, exploratory data analysis, and data visualization, which are crucial for understanding and working with data. As they progress, they will delve into data modeling and analysis, learning about the best practices and tools for creating robust data models and performing predictive analytics.

The course also includes practical lessons on data warehousing and data lakes, and how to manage and secure large datasets. Learners will gain hands-on experience with big data technologies and data engineering principles, including building data pipelines and understanding ETL processes. Modules on data quality and data cleansing will ensure that learners can maintain high standards of data integrity.

Advanced topics such as data mining, machine learning, and predictive modeling are covered in depth, providing learners with the skills to perform complex data analysis and build sophisticated models. Finally, with a strong emphasis on cloud computing, the course prepares learners to leverage the power of cloud platforms for data management and analytics.

Overall, the CDP Certified Data Developer course is designed to provide a solid foundation and advanced knowledge in data science, ensuring learners are well-prepared to tackle real-world data challenges and excel in the field of data development.

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  • Live Training (Duration : 40 Hours)
  • Per Participant

♱ Excluding VAT/GST

Classroom Training price is on request

You can request classroom training in any city on any date by Requesting More Information

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Course Prerequisites

To successfully undertake the CDP Certified Data Developer course, the following minimum prerequisites are recommended:


  • Basic understanding of programming concepts (preferably in Python, Java, or Scala)
  • Familiarity with database systems and SQL (Structured Query Language)
  • Fundamental knowledge of statistics and mathematical concepts
  • Awareness of core computer science concepts such as algorithms and data structures
  • Basic proficiency with spreadsheet tools like Microsoft Excel
  • A willingness to learn new tools and technologies relevant to data science and big data
  • Some exposure to or interest in data analysis and visualization
  • An analytical mindset with problem-solving skills

These prerequisites are intended to provide a foundation for the extensive topics covered in the course. However, individuals with a keen interest in data science and a commitment to learning can often overcome gaps in their knowledge through dedication and hard work.


Target Audience for CDP Certified Data Developer

The CDP Certified Data Developer course is designed for IT professionals looking to master data science, engineering, and analytics.


  • Data Scientists
  • Data Analysts
  • Data Engineers
  • Business Intelligence Professionals
  • Machine Learning Engineers
  • Big Data Architects
  • Database Administrators
  • Software Developers interested in data-oriented roles
  • IT Project Managers overseeing data projects
  • Cloud Computing Specialists
  • ETL (Extract, Transform, Load) Developers
  • Data Quality Analysts
  • Data Governance Specialists
  • Research Scientists (in fields that rely on data analysis)
  • Statisticians looking to upgrade to data science roles
  • AI (Artificial Intelligence) Professionals
  • Professionals working on Data Warehousing and Data Lakes
  • Individuals aiming for roles in Data Security and Data Privacy
  • Technology Consultants involved in data solutions
  • Digital Transformation Experts
  • Analytics Managers
  • Chief Data Officers (CDOs)
  • Entrepreneurs who manage data-driven businesses


Learning Objectives - What you will Learn in this CDP Certified Data Developer?

Brief Introduction to Learning Outcomes and Concepts Covered:

This comprehensive CDP Certified Data Developer course equips learners with advanced skills in data science, modeling, warehousing, visualization, governance, big data, engineering, and analytics for practical industry application.

Learning Objectives and Outcomes:

  • Understand fundamental and advanced data science concepts to collect, analyze, and interpret complex datasets.
  • Acquire the ability to perform data collection, cleaning, preprocessing, and exploratory data analysis for informed decision-making.
  • Master data visualization techniques to effectively communicate data-driven insights using various tools and dashboards.
  • Develop skills in feature engineering and machine learning algorithms to build, evaluate, and optimize predictive models.
  • Gain expertise in data modeling, warehousing, and lakes, including architecture, ETL processes, and performance tuning.
  • Learn best practices in data governance and security to ensure data integrity, privacy, and compliance with regulatory standards.
  • Explore big data technologies, such as Hadoop, Spark, and NoSQL databases, and understand their applications in handling large-scale data.
  • Cultivate the ability to design and manage robust data pipelines, perform data integration, and apply ETL techniques for diverse data engineering tasks.
  • Delve into advanced analytics, predictive modeling, and machine learning to uncover hidden patterns and forecast future trends.
  • Understand cloud computing paradigms, platforms, and data management, including cost and performance optimization for scalable data solutions.

Target Audience for CDP Certified Data Developer

The CDP Certified Data Developer course is designed for IT professionals looking to master data science, engineering, and analytics.


  • Data Scientists
  • Data Analysts
  • Data Engineers
  • Business Intelligence Professionals
  • Machine Learning Engineers
  • Big Data Architects
  • Database Administrators
  • Software Developers interested in data-oriented roles
  • IT Project Managers overseeing data projects
  • Cloud Computing Specialists
  • ETL (Extract, Transform, Load) Developers
  • Data Quality Analysts
  • Data Governance Specialists
  • Research Scientists (in fields that rely on data analysis)
  • Statisticians looking to upgrade to data science roles
  • AI (Artificial Intelligence) Professionals
  • Professionals working on Data Warehousing and Data Lakes
  • Individuals aiming for roles in Data Security and Data Privacy
  • Technology Consultants involved in data solutions
  • Digital Transformation Experts
  • Analytics Managers
  • Chief Data Officers (CDOs)
  • Entrepreneurs who manage data-driven businesses


Learning Objectives - What you will Learn in this CDP Certified Data Developer?

Brief Introduction to Learning Outcomes and Concepts Covered:

This comprehensive CDP Certified Data Developer course equips learners with advanced skills in data science, modeling, warehousing, visualization, governance, big data, engineering, and analytics for practical industry application.

Learning Objectives and Outcomes:

  • Understand fundamental and advanced data science concepts to collect, analyze, and interpret complex datasets.
  • Acquire the ability to perform data collection, cleaning, preprocessing, and exploratory data analysis for informed decision-making.
  • Master data visualization techniques to effectively communicate data-driven insights using various tools and dashboards.
  • Develop skills in feature engineering and machine learning algorithms to build, evaluate, and optimize predictive models.
  • Gain expertise in data modeling, warehousing, and lakes, including architecture, ETL processes, and performance tuning.
  • Learn best practices in data governance and security to ensure data integrity, privacy, and compliance with regulatory standards.
  • Explore big data technologies, such as Hadoop, Spark, and NoSQL databases, and understand their applications in handling large-scale data.
  • Cultivate the ability to design and manage robust data pipelines, perform data integration, and apply ETL techniques for diverse data engineering tasks.
  • Delve into advanced analytics, predictive modeling, and machine learning to uncover hidden patterns and forecast future trends.
  • Understand cloud computing paradigms, platforms, and data management, including cost and performance optimization for scalable data solutions.