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Certified Analytics Professional (CAP) Exam Prep Course

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EDUCBA Bridging the Gap

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  • 1 - CAP certification and Benefits.mp4
    10:29
  • 2 - Different Objectives and their Weightage.mp4
    10:42
  • 3 - Objective Business Problem Framing.mp4
    06:30
  • 4 - Objective Analytical Problem Framing.mp4
    06:30
  • 5 - Objective Methodology Approach.mp4
    06:54
  • 6 - What are Knowledge Statements.mp4
    09:35
  • 7 - Knowledge Statements Presentation techniques.mp4
    06:01
  • 8 - Business problem identification and stakeholders analysis.mp4
    10:05
  • 9 - How to refine problem statement.mp4
    07:26
  • 10 - Initial business benefits and stakeholders agreement.mp4
    04:45
  • 11 - How to Write a problem Statement.mp4
    06:06
  • 12 - Problem Statement Issue Vision etc.mp4
    05:30
  • 13 - Problem Solving.mp4
    03:54
  • 14 - The Problem Definition Process.mp4
    08:52
  • 15 - Power of Reframing Problems.mp4
    03:33
  • 16 - Power of Reframing Problem continued.mp4
    08:31
  • 17 - Business Problem Framing Questions.mp4
    10:10
  • 18 - Analytical Problem Framing.mp4
    09:05
  • 19 - Kanos Requirement Model.mp4
    07:18
  • 20 - Proposed set of drivers and relationship to inputs.mp4
    09:37
  • 21 - Key Metrics of Success.mp4
    11:43
  • 22 - Data Science Introduction and difference between BI and Data Science.mp4
    09:47
  • 23 - Data Science Introduction and difference between BI and Data Science continued.mp4
    06:13
  • 24 - How Data Science Work along with Acquire and Prepare Steps.mp4
    06:43
  • 25 - How Data Science Work along with Acquire and Prepare Steps continued.mp4
    07:09
  • 26 - How to Analyse and Act Data.mp4
    06:41
  • 27 - Guiding Principles and Reasoning and Common Sense.mp4
    11:59
  • 28 - Components of Data Science.mp4
    06:13
  • 29 - Classes of Analytic Techniques Transforming Learning and Predictive Analytics.mp4
    10:11
  • 30 - Learning Models Execution Models Scheduling and Sequencing.mp4
    09:00
  • 31 - Decomposing Analytical Problem.mp4
    11:00
  • 32 - Data Science Maturity.mp4
    06:17
  • 33 - Feature Engineering Dimensionality Reduction and Model Validation Part 1.mp4
    08:25
  • 34 - Feature Engineering Dimensionality Reduction and Model Validation Part 2.mp4
    04:00
  • 35 - DATA CAP Questions.mp4
    07:20
  • 36 - The Five E for CAP exam.mp4
    05:40
  • 37 - The Five E for CAP exam continued.mp4
    06:52
  • 38 - Soft Skills for CAP exam.mp4
    11:18
  • 39 - Clarifying the Analytical Process.mp4
    08:54
  • 40 - CAP Terminology Yield Vechile Routing Problem and TSP.mp4
    10:15
  • 41 - CAP Terminology supply chain six sigma RFM.mp4
    06:24
  • 42 - CAP Terminology supply chain six sigma RFM continued.mp4
    06:31
  • 43 - Pattern Recognition Regression Predictive and Prescriptive Analytics.mp4
    06:06
  • 44 - Pattern Recognition Regression Predictive and Prescriptive Analytics continued.mp4
    06:29
  • 45 - Data Visualization Definition and Importance.mp4
    07:41
  • 46 - Data Visualization Definition and Importance continued.mp4
    06:23
  • 47 - Common Techniques for Data VisualizationData Cardinality and Velocity.mp4
    08:03
  • 48 - Common Techniques for Data VisualizationData Cardinality and Velocity Continued.mp4
    08:02
  • 49 - Decision Trees Heat Maps and other type of Data Visualization Techniques.mp4
    11:49
  • 50 - How to write Data Story.mp4
    10:45
  • 51 - Data Cleaning.mp4
    11:43
  • 52 - Quality of Data and Datamart.mp4
    08:53
  • 53 - Quality of Data and Datamart continued.mp4
    06:52
  • 54 - CAP Terminology Optimization and Next Best offer.mp4
    04:31
  • 55 - Analytics Methodology Introduction.mp4
    11:00
  • 56 - Different type of Analytics Methodology.mp4
    10:01
  • 57 - Software Tool Selection.mp4
    09:01
  • 58 - Validating Analytics Model and Testing Results.mp4
    09:00
  • 59 - Predictive Methodlogy and Different Kinds.mp4
    04:47
  • 60 - Simulation and its Kind.mp4
    04:00
  • Description


    Master the skills and knowledge to ace the CAP exam and advance your career as a Certified Analytics Professional!

    What You'll Learn?


    • Understanding the CAP certification process and its benefits.
    • Mastering business problem framing and analytical problem-solving techniques.
    • Gaining proficiency in data science, including data acquisition, preparation, analysis, and feature engineering.
    • Applying the Five E's of the CAP exam and developing essential soft skills for the certification.
    • Effectively using data visualization tools to communicate insights and create impactful data stories.
    • Learning different analytics methodologies, validating models, and using predictive and simulation techniques.
    • Familiarizing with CAP-specific terminology and concepts like regression, predictive, and prescriptive analytics.
    • By the end of the course, students will be fully equipped to pass the CAP exam and advance their careers in the field of analytics.

    Who is this for?


  • Aspiring Analysts: Individuals looking to start a career in analytics and seeking to obtain the Certified Analytics Professional (CAP) certification.
  • Data Science Professionals: Those currently working in data science or related fields who wish to deepen their understanding of analytics methodologies and improve their skills.
  • Business Professionals: Managers and decision-makers who want to enhance their analytical skills to make data-driven decisions within their organizations.
  • Students: University or college students pursuing degrees in business, data science, statistics, or related fields who are interested in gaining practical knowledge and certification in analytics.
  • Career Changers: Professionals from non-analytical backgrounds seeking to transition into data analytics roles and wanting a comprehensive understanding of the analytics process.
  • What You Need to Know?


  • Basic Understanding of Analytics: A foundational knowledge of data analytics concepts and methodologies is recommended to facilitate comprehension of advanced topics.
  • Familiarity with Data Science Tools: Prior experience with data analysis tools and software (e.g., Excel, R, Python, or SQL) will be beneficial.
  • Statistical Knowledge: A basic understanding of statistical principles and methods is essential for grasping analytical problem framing and interpretation.
  • Critical Thinking Skills: Students should possess strong analytical and critical thinking skills to effectively identify and solve business problems.
  • Desire to Obtain CAP Certification: A motivation to pursue the Certified Analytics Professional (CAP) certification will enhance engagement and commitment to the course material.
  • More details


    Description

    Introduction:

    The Certified Analytics Professional (CAP) certification is a globally recognized credential that validates your expertise in analytics. This course is designed to help you master the essential topics and skills needed to excel in the CAP exam. You will gain insights into business problem framing, analytical problem-solving, data science, and the importance of data visualization. Whether you are an aspiring data scientist, an analytics professional, or someone aiming to advance their career with a CAP certification, this course offers structured learning to help you succeed.

    Section 1: Introduction to CAP Exams

    The course begins with an introduction to the CAP certification, outlining the benefits of earning this credential for analytics professionals. You'll gain a deep understanding of the CAP certification process and how it can boost your career. Additionally, you'll learn the relevance of the certification across different industries and how it serves as a benchmark for analytic skills.

    Section 2: Understanding Objectives

    In this section, you will dive into the key objectives of the CAP exam and their respective weightages. Lectures cover topics such as business problem framing, analytical problem framing, and the methodological approach to solving business challenges. The concept of "knowledge statements" and effective presentation techniques will also be explored, helping you understand what the exam evaluators are looking for.

    Section 3: Understanding Business Problem Identification

    This section focuses on the critical task of identifying business problems and conducting stakeholder analysis. You’ll learn how to refine problem statements and agree on initial business benefits with stakeholders. The goal is to ensure that you can clearly define problems before jumping into analytical solutions.

    Section 4: Further Reading on Business Problem Framing

    Here, you will be guided through the process of writing effective problem statements. This section emphasizes problem-solving techniques, the process of defining a problem, and the powerful impact of re-framing problems. You'll be equipped with questions to frame business problems more effectively, setting the stage for impactful analytical work.

    Section 5: Analytical Problem

    This section delves into the process of analytical problem framing and introduces you to frameworks such as Kano’s Requirement Model. You’ll explore key success metrics, how to propose drivers and relationships between inputs, and understand the core principles that guide successful analytics problem framing.

    Section 6: Certified Analyst Professional Training – Data Science

    Data science plays a crucial role in CAP certification. This section covers data science fundamentals and explores the differences between business intelligence (BI) and data science. You’ll learn the step-by-step process of acquiring and preparing data, analyzing it, and transforming data into actionable insights. Key concepts like feature engineering, dimensionality reduction, and model validation are also discussed.

    Section 7: Certified Analyst Professional Training – Five E’s of CAP Exam

    This section introduces the Five E’s of the CAP exam, focusing on the key skills and soft skills required to pass the exam. You’ll learn how to clarify the analytical process, understand CAP-specific terminology, and apply regression, predictive, and prescriptive analytics. Real-world examples will demonstrate the practical applications of these skills.

    Section 8: Data Visualization – CAP Certification

    In this section, you’ll explore the importance of data visualization in presenting analytics results. Learn common data visualization techniques such as decision trees and heat maps, and how to effectively communicate data insights through data storytelling. Data quality, cleaning, and building a data mart are also discussed, providing you with the tools to create meaningful, accurate visual representations.

    Section 9: Analytics Methodology and Test Analytics Model

    The final section focuses on different analytics methodologies and how to validate analytics models. You'll learn about predictive methodologies, simulation techniques, and software tool selection. This section ensures you are prepared to test, refine, and implement analytics models in a real-world context.

    Conclusion:

    By the end of this course, you will have a solid understanding of the key components required to excel in the CAP exam. You will be proficient in framing business and analytical problems, applying data science techniques, utilizing data visualization tools, and validating analytics models. This comprehensive training will equip you with the skills necessary to become a Certified Analytics Professional.

    Who this course is for:

    • Aspiring Analysts: Individuals looking to start a career in analytics and seeking to obtain the Certified Analytics Professional (CAP) certification.
    • Data Science Professionals: Those currently working in data science or related fields who wish to deepen their understanding of analytics methodologies and improve their skills.
    • Business Professionals: Managers and decision-makers who want to enhance their analytical skills to make data-driven decisions within their organizations.
    • Students: University or college students pursuing degrees in business, data science, statistics, or related fields who are interested in gaining practical knowledge and certification in analytics.
    • Career Changers: Professionals from non-analytical backgrounds seeking to transition into data analytics roles and wanting a comprehensive understanding of the analytics process.

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    EDUCBA Bridging the Gap
    EDUCBA Bridging the Gap
    Instructor's Courses
    EDUCBA is a leading global provider of skill based education addressing the needs of 1,000,000+ members across 70+ Countries. Our unique step-by-step, online learning model along with amazing 5000+ courses and 500+ Learning Paths prepared by top-notch professionals from the Industry help participants achieve their goals successfully. All our training programs are Job oriented skill based programs demanded by the Industry. At EDUCBA, it is a matter of pride for us to make job oriented hands-on courses available to anyone, any time and anywhere. Therefore we ensure that you can enroll 24 hours a day, seven days a week, 365 days a year. Learn at a time and place, and pace that is of your choice. Plan your study to suit your convenience and schedule.
    Students take courses primarily to improve job-related skills.Some courses generate credit toward technical certification. Udemy has made a special effort to attract corporate trainers seeking to create coursework for employees of their company.
    • language english
    • Training sessions 60
    • duration 7:55:14
    • Release Date 2025/01/16