Healthcare Data Analytics

Health Data Analytics internship will equip interns with skills in working with health data using predictive analytics enabled by machine learning (ML) tools that can be used to predict something about the future of a patient from historical health data. It could also be investigating a large population to determine causes of illnesses using electronic health record data or to help identify the best therapy choices for patients based on their historic health data. In this internship, you will build end-to-end projects using data analysis and machine learning to implement simple-to-complex healthcare analytics tasks to automate health insights and improve healthcare delivery.

Health Data Analytics internship is aimed at trainees from diverse backgrounds such as health-related or medical domains, including clinical or lab scientists, as well as people from biological sciences. Any other domain is also accepted, provided you have an interest in healthcare.

What you will Gain from the Healthcare Data Analytics:

  • ● Supportive and innovative teaching
  • ● Extra One-On-One support sessions weekly
  • ● Practical teaching from resourceful and internationally trained instructors
  • ● Certification and Solid Health Analytics Project portfolio
  • ● Employability skills and Interview Preparation
  • ● Career Newsletter
  • ● Course content that aligns with health analytics internationally.

Areas you will learn:

  • ● Analysis of healthcare data using various state-of-the-art techniques
  • ● Hands-on machine learning algorithms use in healthcare
  • ● Application of machine learning techniques to understand various diseases
  • ● Application of visualizations to understand healthcare data
  • ● How Artificial Intelligence can be used for healthcare
  • ● How machine learning can be used to develop health intelligence applications

Technology Tools you will Learn in this Internship:

  • ● Python Programming
  • ● SQL
  • ● Power BI

Course Outlines

Statistics for Health Data Analytics

Understanding Statistics in Plain English
When to Use a Particular Statistical Test

Python and Application Programming for Healthcare

You will learn to understand decision support systems using data insights. You will work your way up from learning to code, and application development to leveraging data to automate decision-making processes across the healthcare industry and medical diagnosis and the end-to-end process of it.

Introduction to Healthcare Data
Git and GitHub for Version Control
Data Types, Arithmetic Operations, Python Lists, and List Comprehension
Conditional Statements (If Else, Elif, For Loops and While Loops)
Python Function Basics to Advanced
Building Python Applications in Healthcare
Deploying Python Application in Healthcare
Working with Numpy for Numeric Computing
Working with Pandas for Medical Data Analysis
Data Quality Assessment, Cleaning and Transformation
Exploratory Data Analysis (EDA)
EDA Data Visualization
Data Visualization of Medical Images
Introduction to Data Analytics in Healthcare Industry
Introduction to Machine Learning and Machine Learning Algorithms
Introduction to AI in Healthcare
Signal Processing with Healthcare Data
Machine Learning with Healthcare Data (Various Projects)
Deep Learning with Healthcare Data
Medical Image Analysis Using Deep Learning (Various Projects)


Microsoft Power BI training will equip you with powerful skills for visualizing data from various sources by aggregating them on a dashboard for data-driven insights. You will build a fully interactive health intelligence report and dashboard for a real-life use case.

Introduction to Power BI for Decision Intelligence:
– Overview of Power BI and its significance in decision-making.
– Understanding the Power BI interface and its core features.
– Exploring data visualization concepts and best practices.

Introduction to Power BI for Decision Intelligence:
– Overview of Power BI and its significance in decision-making.
– Understanding the Power BI interface and its core features.
– Exploring data visualization concepts and best practices.
Data Preprocessing and Transformation in Power BI:
– Importing data from various sources into Power BI.
– Data cleaning, formatting, and handling missing values.
– Applying data transformation techniques to optimize data for analysis.
Introduction to Relationships and Model:
– Understanding the importance of data relationships in Power BI.
– Creating and managing relationships between different data tables.
– Designing an efficient data model for enhanced analysis capabilities.
More on Data Preprocessing and Transformation:
– Advanced data shaping techniques using Power Query Editor.
– Combining and merging data from multiple sources.
– Handling complex data transformations and calculations.
Introduction to DAX, Measures, and Calculated Columns:
– Introduction to the Data Analysis Expressions (DAX) language
– Creating measures and calculated columns for data analysis.
– Applying DAX functions to perform advanced calculations and aggregations.
Creating Data-Intelligent Visualization Reports and Dashboards:
– Designing visually appealing and interactive reports.
– Implementing various types of visualizations, such as charts, tables, and maps.
– Utilizing advanced features, such as slicers, drill-through, and bookmarks.


In this practical course, you will gain essential skills in working with SQL, the language of databases. You will learn how to effectively query databases, extract data, and transform it for further analysis. By mastering SQL, you will become proficient in managing and manipulating data stored in relational databases.

Introduction to Relational Database Management System:
– Understanding the fundamentals of relational databases.
– Exploring the components and structure of a database.
– Getting familiar with key database concepts, such as tables, columns, and relationships.
Hands-on MySQL Database:
– Setting up and configuring a MySQL database for practical exercises.
– Navigating and interacting with the MySQL command-line interface.
– Executing basic SQL queries to retrieve and manipulate data.
Creating SQL Database:
– Designing and creating a SQL database using appropriate data types and constraints.
– Defining primary keys, foreign keys, and relationships between tables.
– Ensuring data integrity and normalization principles.
Grouping and Summarizing Data with SQL:
– Using SQL’s aggregate functions (e.g., SUM, AVG, COUNT) to summarize data.
– Grouping data based on specific criteria for meaningful analysis.
– Applying filters and conditions to aggregate data effectively.
Using SQL to Select Data from More Than One Table:
– Understanding the concept of table joins in SQL.
– Utilizing different join types (e.g., INNER JOIN, LEFT JOIN, RIGHT JOIN) to combine data from multiple tables.
– Writing complex queries involving multiple tables to extract relevant information.
Using SQL Views:
– Creating and utilizing SQL views to simplify complex queries.
– Understanding the benefits and practical applications of views.
– Modifying and updating data through views.
Using SQL Sub-Queries:
– Leveraging sub-queries to perform nested and correlated queries.
– Incorporating sub-queries in various parts of a SQL statement.
– Applying sub-queries for advanced filtering and data manipulation.
Using SQL to Insert, Update, and Delete Data:
– Inserting new records into a database using SQL’s INSERT statement.
– Updating existing data using SQL’s UPDATE statement.
– Deleting unwanted data using SQL’s DELETE statement.
Using SQL Transactions:
– Understanding the concept of transactions in database operations.
– Implementing transaction control statements (BEGIN, COMMIT, ROLLBACK) to ensure data consistency and integrity.
– Handling errors and managing transactional operations effectively.


  • Face-to-Face Program (Only Available in Abuja, Nigeria). Class Schedules: Monday, Wednesday and Thursday (10 am – 3 pm).
  • Online Program (All Locations, Classes are in the Evening): Register to get specific time schedules.



  • ● U.K (Instructors Only teach Online Classes)
  • ● U.S/CANADA (Instructors Only teach Online Classes)
  • ● Abuja, Nigeria (Instructors teach both Face-to-Face and Online Classes)

Note: This program will have instructors from a combination of these locations. You will normally be expected to be taught by instructors from any of these locations.

REGISTRATION: Fill out the Form Below to Register and to Receive the Course Fee with a very Flexible Instalment Plan.

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