Deep Data Dive (Data Science and Machine Learning)
Master the power of DATA! In this beginner-friendly, project-driven course, you’ll master Python for data analysis, R, SQL, and cutting-edge machine learning ...
Master the power of DATA! In this beginner-friendly, project-driven course, you’ll master Python for data analysis, R, SQL, and cutting-edge machine learning ...
Unlock the career defining skill set that today’s employers crave without the intimidation factor. “Data Science & Machine Learning” is an eight-week, beginner friendly journey that starts with the building blocks of Python, R, SQL, and Git, then guides you step by step to advanced machine learning techniques and real-world deployment. Each week layers practical skills onto the last: from spotless data wrangling and eye-catching visualizations to statistics that separate signal from noise and models that predict the future with confidence.
But this course is more than a syllabus; it’s an immersive, project driven experience. You’ll clean messy datasets, craft interactive dashboards, and train algorithms on problems drawn straight from industry. Weekly recorded labs accelerate your learning, while a mentor-guided capstone lets you showcase end-to-end mastery, ready for your portfolio and recruiters’ inboxes.
By the final presentation in Week 8, you won’t just know data science; you’ll have proven it, with deployable code, compelling insights, and the confidence to speak the language of data at any interview or boardroom. Join us and convert curiosity into career changing capability.
Introduction to Data Analysis/Science & Career Paths
Python for Data Analysis: Syntax, Variables, Loops
R for Data Analysis: Syntax, Data Frames, Functions
SQL Server for Data Analysis: Syntax & Functions
GitHub Workflow + Hello Python/R Notebooks
3:1:0Resources
Setting Up: Jupyter, RStudio, IDEs, SSMS
00:60:00Laptop, Stable Internet, Zoom/Google Meet
Understand the full data science workflow and career roles
Write and debug code in Python and R
Clean and transform data using Pandas and Tidyverse
Perform data analysis
Visualize data using Matplotlib, Seaborn, and ggplot2
Communicate insights with clear visuals and storytelling
Apply statistics: descriptive, inferential, and hypothesis testing
Build and evaluate basic machine learning models
Complete and present a real-world data science capstone project
Create a GitHub portfolio to showcase your skills
 
            
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 5 Students
            5 Students
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        Senior Data Engineer (Health Systems) | Software Engineer | ETL & Data Warehouse Specialist
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                    Students
5 
                    language
English 
                    Duration
14h 11mLevel
beginnerExpiry period
6 MonthsCertificate
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                     English
                                English
                             Certificate Course
                                Certificate Course
                             5 Students
                                5 Students
                             14h 11m
                                14h 11m