Mentor Based
Advanced Data Visualization Techniques With Pandas Matplotlib Seaborn and Healthcare Data
Live Registration
BATCH #24
03Seats Left
92% Booked
02
Days
:
00
Hrs
:
00
Min
:
00
Sec
Course Overview
Program Syllabus
Module 1
About This Course
The Advanced Data Visualization Techniques program is crafted to deepen the understanding and application of data visualization tools among advanced scholars and professionals. This course focuses on the practical and strategic use of Pandas, Matplotlib, and Seaborn, with a specialized emphasis on healthcare data, providing participants the skills to visualize complex datasets and communicate findings effectively.
Module 2
Aim
This program aims to equip PhD scholars and academicians with unparalleled expertise in data visualization using Pandas, Matplotlib, and Seaborn, tailored specifically for healthcare data. The curriculum is designed to foster advanced analytical skills, enhance visual storytelling capabilities, and prepare participants to lead data-driven decisions in research and clinical environments.
Module 3
Program Objectives
- Master the use of Pandas, Matplotlib, and Seaborn for advanced data visualization.
- Apply data visualization techniques to interpret and analyze healthcare data.
- Develop interactive visualizations to facilitate dynamic data exploration.
- Enhance ability to communicate complex analytical results to non-technical stakeholders.
- Lead and innovate in data visualization within the healthcare sector.
Module 4
Module 1: Introduction to Advanced Data Visualization
- Principles of Data Visualization
- Review of Tools: Pandas, Matplotlib, Seaborn
- Emerging Trends in Visualization
- AI-driven visual analytics
- Augmented Reality (AR) for data presentation
Module 5
Module 2: Advanced Data Handling with Pandas
- Advanced Data Manipulation Techniques
- Time-Series Data Analysis for Healthcare Datasets
- Handling Big Data
- Techniques for managing and visualizing large-scale datasets efficiently
Module 6
Module 3: Creating Visualizations with Matplotlib
- Advanced Plotting Techniques
- Customizing Plots for Scientific Communication
- Automation of Plot Adjustments
- Using scripts to dynamically adjust visualizations based on user interaction or data changes
Module 7
Module 4: Statistical Data Visualization with Seaborn
- Visualization of Statistical Models
- Multi-Variable Analysis for Complex Data Sets
- Advanced Statistical Plots
- Integrating complex statistical concepts into visualizations to enhance interpretation
Module 8
Module 5: Interactive and Real-Time Visualization
- Building Interactive Dashboards with Plotly
- Real-Time Data Visualization Strategies
- Streaming Data Visualization
- Techniques for visualizing streaming data in real-time for immediate decision-making
Module 9
Module 6: Healthcare Data Application
- Case Studies: Visualizing Clinical Trial Data
- Public Health Data Visualization and Reporting
- Visual Epidemiology
- Using visualization techniques to track and predict disease outbreaks
Module 10
Module 7: Capstone Project
- Integrating Visualization Tools to Analyze a Large Healthcare Dataset
- Presentation of Insights and Strategic Recommendations
- Data Storytelling
- Crafting compelling narratives with data to influence health policy and patient care strategies
Module 11
Module 8: Ethical Implications of Data Visualization
- Transparency and Bias in Visual Representations
- Addressing how visual design choices can influence perception and decisions
- Ethical Use of Healthcare Data
- Ensuring patient privacy and data security in visualization projects
Module 12
Who Should Enrol?
Targeted at professionals and academics with a background in data science, biostatistics, or healthcare analytics, this program requires foundational knowledge in Python programming and basic statistics.
Module 13
Program Outcomes
- Proficient in advanced data visualization techniques.
- Skilled in handling and visualizing complex healthcare datasets.
- Capable of designing interactive data presentations.
- Equipped to lead data-centric projects in healthcare environments.
- Ready to communicate intricate data insights effectively.
Module 15
What You’ll Gain
- Full access to e-LMS
- Real-world dry lab projects
- 1:1 project guidance
- Publication opportunity
- Self-assessment & final exam
- e-Certificate & e-Marksheet
Module 16
Join Our Hall of Fame!
Take your research to the next level with NanoSchool.
Module 17
Publication Opportunity
Get published in a prestigious open-access journal.
Module 18
Centre of Excellence
Become part of an elite research community.
Module 19
Networking & Learning
Connect with global researchers and mentors.
Module 20
Global Recognition
Worth ₹20,000 / $1,000 in academic value.
Module 21
View All Feedbacks →
Need Help?
We’re here for you!
★★★★★
Generative AI and GANs
António Ricardo de Bastos Teixeira • ★★★★★
AI for Environmental Monitoring and Sustainablility
Mladen Kulev • ★★★★★
Prediction of Protein Structure Using AlphaFold: An Artificial Intelligence (AI) Program
Antonio Mauceri • ★★★★★
Green Catalysts 2024: Innovating Sustainable Solutions from Biomass to Biofuels
MIKESON V S • View All Feedbacks →
Lead Instructor
Dr. Sarah Chen
PhD in Computational Mechanics from MIT with 15+ years of experience in Industrial AI. Former Lead Data Scientist at Tesla and current advisor to Fortune 500 manufacturing firms.
Enroll Now
Instant Access
Need Guidance?
Not sure if this course is right for you? Schedule a free 15-minute consultation with our academic advisors.