Quantitative and Qualitative Data Analysis using R, Python, NVIVO, ODK, and Power BI Course
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Quantitative and Qualitative Data Analysis using R, Python, NVIVO, ODK, and Power BI Course

10 Days Online - Virtual Training

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# Start Date End Date Duration Location Registration
9 29/04/2024 10/05/2024 10 Days Live Online Training
10 06/05/2024 17/05/2024 10 Days Live Online Training
11 24/06/2024 05/07/2024 10 Days Live Online Training
12 08/07/2024 19/07/2024 10 Days Live Online Training
13 22/07/2024 02/08/2024 10 Days Live Online Training
14 19/08/2024 30/08/2024 10 Days Live Online Training
15 02/09/2024 13/09/2024 10 Days Live Online Training
16 16/09/2024 27/09/2024 10 Days Live Online Training
17 14/10/2024 25/10/2024 10 Days Live Online Training
18 11/11/2024 22/11/2024 10 Days Live Online Training
19 02/12/2024 13/12/2024 10 Days Live Online Training
20 16/12/2024 27/12/2024 10 Days Live Online Training

Introduction:

Embark on a transformative learning experience with our Quantitative and Qualitative Data Analysis course, where we bring together the power of R, Python, NVIVO, ODK, and Power BI. In this dynamic program, participants will delve into the world of data analytics, mastering both quantitative and qualitative methodologies. This course is tailored for individuals seeking a comprehensive understanding of data analysis, providing a robust skill set to navigate the complexities of modern data-driven decision-making.

As we traverse the realms of R and Python for quantitative insights, delve into NVIVO's qualitative capabilities, harness ODK for efficient data collection, and leverage Power BI for impactful visualizations, participants will gain a holistic perspective on data analysis. Through a blend of theoretical concepts, hands-on exercises, and real-world applications, this course ensures that learners not only grasp the intricacies of individual tools but also comprehend how to seamlessly integrate them for a synergistic approach to data analysis. Join us on this educational journey, and unlock the potential of your data like never before.

Course Objectives:

  1. Mastering quantitative analysis techniques with R and Python.
  2. Developing proficiency in qualitative data analysis using NVIVO.
  3. Understanding the application of ODK for efficient data collection.
  4. Harnessing the capabilities of Power BI for insightful data visualization.
  5. Integrating quantitative and qualitative insights for comprehensive analysis.
  6. Building skills in data cleaning, transformation, and preprocessing.
  7. Implementing statistical models for hypothesis testing and prediction.
  8. Gaining hands-on experience in coding for data manipulation and analysis.
  9. Exploring advanced features of NVIVO for in-depth qualitative research.
  10. Creating interactive and compelling data dashboards with Power BI.

Organizational Benefits:

  1. Enhanced decision-making through comprehensive data analysis.
  2. Increased efficiency in data collection and processing using ODK.
  3. Improved accuracy and reliability of organizational data.
  4. Better strategic planning with a combination of qualitative and quantitative insights.
  5. Cost savings through optimized data management processes.
  6. Empowered teams with advanced data analysis skills.
  7. Improved project management through NVIVO's qualitative research capabilities.
  8. Enhanced data visualization for effective communication and reporting.
  9. Strengthened organizational research and development capabilities.
  10. Competitive advantage through informed and data-driven decision-making.

Target Participants:

This course is designed for professionals, researchers, and decision-makers who work with data in various capacities. Whether you are a data analyst, researcher, project manager, or executive, this course will provide valuable insights and skills to enhance your proficiency in data analysis.

Course Outline:

Module 1: Foundations of Data Analysis with R and Python

  1. Introduction to Data Analysis:
    • Overview of data analysis concepts.
    • Importance of data-driven decision-making.
    • Introduction to R and Python for data analysis.
  2. Data Manipulation and Transformation:
    • Exploring data types and structures.
    • Data cleaning techniques.
    • Transforming and reshaping datasets.
  3. Statistical Analysis with R and Python:
    • Descriptive statistics and data summarization.
    • Inferential statistics and hypothesis testing.
    • Regression analysis for predictive modeling.
  4. Data Visualization:
    • Introduction to data visualization principles.
    • Creating plots and charts using ggplot2 (R) and Matplotlib (Python).
    • Interpreting visualizations for insights.
  5. Advanced Analytics with R and Python:
    • Time series analysis.
    • Clustering and classification techniques.
    • Machine learning fundamentals.
  6. Practical Applications and Projects:
    • Applying R and Python to real-world scenarios.
    • Project work integrating data analysis concepts.
    • Collaboration and sharing best practices.

Module 2: Qualitative Data Analysis with NVIVO

  1. Introduction to Qualitative Research:
    • Understanding qualitative research principles.
    • Differentiating between qualitative and quantitative data.
  2. NVIVO Basics:
    • Installation and setup of NVIVO.
    • Importing and organizing qualitative data.
    • Navigating the NVIVO interface.
  3. Coding and Categorization:
    • Fundamentals of coding qualitative data.
    • Creating categories and themes.
    • Ensuring consistency in coding.
  4. Thematic Analysis with NVIVO:
    • Exploring advanced features of NVIVO.
    • Conducting thematic analysis.
    • Extracting meaningful insights from qualitative data.
  5. Visualizing Qualitative Insights:
    • Visualization tools in NVIVO.
    • Creating reports and summaries.
    • Presenting qualitative findings effectively.
  6. Project-based Qualitative Analysis:
    • Applying NVIVO to real-world qualitative datasets.
    • Group projects and collaborative analysis.
    • Feedback and refinement of qualitative research skills.

Module 3: ODK for Efficient Data Collection

  1. Introduction to ODK:
    • Understanding the role of ODK in data collection.
    • Benefits of mobile-based data collection.
  2. Form Design and Deployment:
    • Creating ODK forms for data collection.
    • Uploading forms for deployment.
    • Version control and updates.
  3. Data Collection with ODK Collect:
    • Using ODK Collect in the field.
    • Offline data collection capabilities.
    • Ensuring data accuracy and completeness.
  4. Data Submission and Storage:
    • Uploading collected data to a central server.
    • Ensuring data security and integrity.
    • Managing large datasets efficiently.
  5. Quality Control and Validation:
    • Implementing checks and validations in ODK.
    • Addressing data quality issues in real-time.
    • Troubleshooting common challenges.
  6. Field Implementation and Case Studies:
    • Real-world implementation of ODK in various settings.
    • Case studies showcasing successful data collection.
    • Lessons learned and best practices.

Module 4: Power BI for Data Visualization and Integration

  1. Introduction to Power BI:
    • Overview of Power BI and its capabilities.
    • Connecting to different data sources.
    • Understanding Power BI workspace.
  2. Data Import and Transformation:
    • Importing data into Power BI.
    • Data cleaning and transformation using Power Query.
    • Merging and appending datasets.
  3. Building Interactive Dashboards:
    • Creating basic visualizations in Power BI.
    • Designing interactive dashboards.
    • Implementing filters and slicers for user interaction.
  4. Advanced Data Visualization Techniques:
    • Customizing visuals in Power BI.
    • Using DAX for advanced calculations.
    • Incorporating custom visuals and themes.
  5. Power BI for Business Intelligence:
    • Leveraging Power BI for business analytics.
    • Integrating data from different sources.
    • Creating actionable insights for decision-makers.
  6. Final Project Integration:
    • Bringing together R, Python, NVIVO, ODK, and Power BI.
    • Completing a comprehensive data analysis project.
    • Presentation and discussion of final projects.

General Information

  1. Customized Training: All our courses can be tailored to meet the specific needs of participants.
  2. Language Proficiency: Participants should have a good command of the English language.
  3. Comprehensive Learning: Our training includes well-structured presentations, practical exercises, web-based tutorials, and collaborative group work. Our facilitators are seasoned experts with over a decade of experience.
  4. Certification: Upon successful completion of training, participants will receive a certificate from Foscore Development Center (FDC-K).
  5. Training Locations: Training sessions are conducted at Foscore Development Center (FDC-K) centers. We also offer options for in-house and online training, customized to the client's schedule.
  6. Flexible Duration: Course durations are adaptable, and content can be adjusted to fit the required number of days.
  7. Onsite Training Inclusions: The course fee for onsite training covers facilitation, training materials, two coffee breaks, a buffet lunch, and a Certificate of Successful Completion. Participants are responsible for their travel expenses, airport transfers, visa applications, dinners, health/accident insurance, and personal expenses.
  8. Additional Services: Accommodation, pickup services, freight booking, and visa processing arrangements are available upon request at discounted rates.
  9. Equipment: Tablets and laptops can be provided to participants at an additional cost.
  10. Post-Training Support: We offer one year of free consultation and coaching after the course.
  11. Group Discounts: Register as a group of more than two and enjoy a discount ranging from 10% to 50%.
  12. Payment Terms: Payment should be made before the commencement of the training or as mutually agreed upon, to the Foscore Development Center account. This ensures better preparation for your training.
  13. Contact Us: For any inquiries, please reach out to us at training@fdc-k.org or call us at +254712260031.
  14. Website: Visit our website at www.fdc-k.org for more information.

 

 

 

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