Data Analytics
Healthcare Data Analytics
Master the fundamentals of Data Analytics in this 8-week program designed to equip learners with essential skills to analyze, interpret, and visualize data. You’ll gain hands-on experience with tools such as Excel, R, Python, Tableau, and Power BI. The course covers data cleaning, analysis techniques, and visualization methods to help you draw actionable insights, particularly in the context of healthcare data.
Schedule
- Introduction to the Course: Overview, Objectives, and Expectations
- What is Data Analysis? Role in Decision-Making
- Overview of Tools Covered: Excel, R, Python, Tableau, Power BI
- Installing Data Analysis Tools:
- Download and Install Excel (or Office 365)
- Download and Install R and RStudio
- Download and Install Python (with Anaconda)
- Download and Install Tableau Public
- Download and Install Power BI Desktop
- Basic Data Structures and Concepts
- Real-world Use Cases of Data Analysis in Healthcare
- Overview of Excel for Data Analysis
- Data Importing and Cleaning in Excel
- Pivot Tables and Data Summarization
- Basic Formulas for Data Analysis (SUM, AVERAGE, IF, COUNT)
- Using Excel Charts for Basic Visualization (Bar, Line, Pie)
- Data Validation and Conditional Formatting
- Case Study: Analyzing Patient Admission Data in Excel
- Overview of R Programming Language for Data Analysis
- Setting Up R and RStudio
- Importing and Cleaning Data in R
- Descriptive Statistics in R (Mean, Median, Mode, Variance)
- Data Visualization with ggplot2
- Basic R Programming Syntax (Variables, Loops, Functions)
- Case Study: Analyzing Clinical Trial Data with R
- Overview of Python for Data Science
- Setting Up Python with Anaconda
- Introduction to Pandas for Data Manipulation
- Data Cleaning and Transformation in Python
- Using NumPy for Statistical Analysis
- Data Visualization in Python with Matplotlib and Seaborn
- Case Study: Analyzing Healthcare Cost Data with Python
- Overview of Tableau as a Data Visualization Tool
- Setting Up Tableau Public
- Connecting to Healthcare Data Sources in Tableau
- Creating Basic Visualizations: Bar Charts, Line Graphs, Pie Charts
- Building Dashboards and Storytelling with Data
- Using Filters, Parameters, and Calculated Fields
- Case Study: Creating a Hospital Performance Dashboard in Tableau
- Overview of Power BI for Business Intelligence
- Setting Up Power BI Desktop
- Importing Healthcare Data into Power BI
- Creating Interactive Visualizations: Bar, Scatter, Line, Map
- Building Dashboards and Reports in Power BI
- Data Filtering, Slicing, and Dicing in Power BI
- Case Study: Building a Healthcare Provider Dashboard in Power BI
- Introduction to the Capstone Project
- Data Collection: Patient Data (Age, Gender, Diagnosis, Length of Stay)
- Cleaning and Preparing the Data for Analysis
- Analyzing Trends in Patient Admissions, Diagnoses, and Outcomes
- Visualizing the Data: Pivot Tables, Graphs, Dashboards
- Insights and Recommendations Based on the Data
- Presenting the Final Report with Key Findings and Visualizations
- Introduction to Predictive Analytics in Healthcare
- Data Collection: Medical History, Treatments, Outcomes
- Preparing the Dataset for Predictive Modeling
- Building a Predictive Model (using R or Python)
- Identifying Key Variables that Influence Patient Outcomes
- Using Predictive Models to Forecast Healthcare Costs or Hospital Readmissions
- Visualizing and Presenting Predictive Insights to Healthcare Stakeholders
- Overview of Career Opportunities in Healthcare Data Analysis
- Essential Skills for Healthcare Data Analysts
- Building a Professional Portfolio and Case Studies
- Certifications and Advanced Learning (Tableau, Power BI, Python, R)
- Exploring Career Paths: Data Analyst, Data Scientist, BI Analyst
- Networking and Professional Development (Conferences, Workshops)
- Final Reflections and Course Wrap-U
What's included in your course
Self-Paced Class
Courses are designed to be flexible, allowing participants the freedom to take classes at their own pace. This adaptability not only accommodates busy schedules but also fosters a deeper understanding of the material being covered before moving on to the next topic.
Capstone Project
Engage in hands-on learning through comprehensive projects that consolidate your knowledge and skills. These capstone projects are designed to simulate real-world scenarios, providing practical experience and a deeper understanding of the subject matter.
Certificate of Completion
Upon successfully finishing the course, you'll receive a certificate of completion. This certificate not only acknowledges your dedication and achievement but also serves as a valuable credential to showcase your expertise to potential employers or clients.
Internship
Gain practical experience through internship opportunities that allow you to apply your learning in professional settings. These internships are structured to provide hands-on exposure, enhance your resume, and build a network within your chosen field.
Career Coaching
Benefit from personalized career coaching sessions aimed at guiding you through your professional journey. These sessions offer insights into industry trends, job search strategies, and personal branding, empowering you to make informed career decisions.
Job Search
Access resources and support tailored to assist you in your job search. From resume writing workshops to interview preparation and networking opportunities, you'll be equipped with the tools necessary to navigate the job market effectively and secure positions that align with your career goals.
Frequently Asked Questions
The Data Analysis Course is an 8-week program designed to teach participants how to analyze and interpret data using popular tools like Excel, R, Python, Tableau, and Power BI. It covers fundamental data analysis techniques, data visualization, and real-world applications in healthcare.
The course is 8 weeks long, delivered in a self-paced format. Each week includes practical exercises, tutorials, and projects to help you build your skills in data analysis and visualization.
This course is open to anyone who wants to learn data analysis, whether you’re new to the field or looking to expand your skill set. It’s particularly beneficial for professionals in healthcare, business, or tech who need to work with data.
The course fee is flexible, with an option to split payments into two installments to make it more affordable. The first installment is due at enrollment, and the second halfway through the course.
Yes, you can pay the course fee in two installments. The first payment is required when you sign up, and the second installment is due midway through the program.
If you decide to withdraw from the course within the first week, you’ll be eligible for a full refund. If you withdraw during the second week, you can receive a 50% refund. No refunds will be issued after the second week.
Yes, upon successful completion of the course, you’ll receive a certificate of completion. This certificate verifies your proficiency in data analysis and can be used to enhance your resume or LinkedIn profile.
Anyone looking to develop data analysis skills can benefit from this course. It’s ideal for healthcare professionals, data analysts, business analysts, and anyone interested in using data to make informed decisions.
Yes, the course is entirely online, so you can participate from anywhere in the world. The self-paced format allows you to learn on your own schedule, making it accessible regardless of your time zone or availability.