Career Path

Data Science

Data-driven decision-making is the ultimate competitive advantage for businesses and governments worldwide. Data Science provides lucrative career opportunities that will continue to expand.

Industry analysis shows a 650% Data Science job growth since 2012, with an estimated 11.5 million new jobs projected by 2026. This course aims to provide students with the latest job-ready tools and skills, including open source tools and libraries. Learn data science through lectures and hands-on practice using real data science tools and real-world data sets.

What you will learn?

Data Loading and Integration Techniques

This session focuses on techniques for importing various data formats into R. Students will learn to work with CSV, Excel, JSON, and SQL databases using packages like {readr}, {readxl}, {jsonlite}, and {DBI}.

Data Cleaning and Preprocessing

Data quality challenges are addressed in this session. Students learn to identify and handle missing values, outliers, and inconsistencies in their datasets using the {tidyr} and {dplyr} packages.

Introduction to Modern Data Science with R and LLMs

This first session establishes the foundational concepts of data science and introduces the R ecosystem. Students will set up their R environment, including RStudio and essential packages.

Exploratory Data Analysis with the Tidyverse

This session introduces the powerful Tidyverse ecosystem for exploratory data analysis in R. Students will master {dplyr} for data manipulation, learning to filter, select, mutate, summarize, and group data efficiently.

Advanced Data Visualization with ggplot2

Effective data visualization techniques are the focus of this session, with an emphasis on creating plots that tell compelling stories about economic data.

Statistical Analysis and Modeling

This session introduces statistical techniques commonly used in economic analysis. Students will learn to perform hypothesis testing, correlation analysis, and regression modeling using R packages like {stats}, {car}, and {lmtest}.

Machine Learning Fundamentals with tidymodels

This session introduces machine learning concepts using the {tidymodels} framework in R. Students will learn about supervised and unsupervised learning approaches relevant to economic data analysis, including classification, regression, and clustering algorithms.

Automating Data Workflows with Targets

This session focuses on creating reproducible, automated data science workflows using the {targets} package in R. Students will learn to build data pipelines that efficiently manage dependencies between data processing steps.

Creating Reports and Documents with Quarto

This session introduces Quarto as a powerful tool for creating dynamic, reproducible documents that combine code, results, and narrative. Students will learn to create professional reports, presentations, and dashboards that effectively communicate their data insights.

Building Interactive Applications with Shiny

The final session introduces {shiny} for creating interactive web applications that allow users to engage with data analyses without coding knowledge. Students will learn the basics of reactive programming and how to build user interfaces that showcase their project findings.

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Experiential learning with
success-based pricing

Better price point than similar programs. Superior value with 10x guaranteed results.

Tuition starts at

¢4,800

Learn in-demand digital skills at subsidized costs.

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Tuition fee refundable if no value is delivered after 7 days of enrolment. Ts & Cs Apply.

Weekly progress reports personalized to each learner.

Access to real projects and custom learning paths.

Dedicated coach support throughout your learning journey.

Lifetime access to SFAN network and platforms.

Platform-generated transcript to demonstrate job readiness.

Uninhibited access to our interactive course framework.

Custom resume at program completion for top students.

A verified certificate upon successful graduation from the program.

Elevator pitch video for select high performing students.

AI-assisted career support to bridge networks.

Program Schedule

Week 0

ONBOARDING

Week 1

FOUNDATIONAL

Week 2

DISCOVERY

Week 3

HANDS-ON

Week 4-10

UPSCALE

Week 11

CAPSTONE

Week 12

PRESENTATION

12 Weeks, Blended

Experience

Entry-Level
Mid-Level

Must Have

Laptop and a stable internet connection.
15 hours weekly to actively participate.
Bachelor's degree in Computer science, Social sciences, or Statistics.

Bonus Courses

This track has complementary courses, such as Email Writing, Attention to Detail, Design Thinking and How to Apply for Digital Jobs.

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Re-inventing learning Re-inventing learning

Understand how you stack up against your competition.

Level up with tailored learning resources from subject-matter experts.

Build confidence and demonstrate career readiness in ways traditional systems fail to do.

Connect with mentors, recruiters, industry professionals, and co-dreamers, bypassing traditional barriers.

Learn from practitioners

Laurent Smeets

10+ years of Data Science experience.

Testimonies

Dolly Kpobi,

UX/UI Designer

I will describe my ReadyforWork experience as impactful. As a recent graduate trying to navigate the job space, I've received the confidence boost I needed from the ReadyforWork digital career accelerator. I highly recommend ReadyforWork to individuals trying to find their feet in the job space.

Girard Boakye-Yiadom,

Digital Marketer

ReadyforWork cohort 4 has been a good experience and very insightful. I learned many things I didn't know that I thought I knew initially. I highly recommend this program to anyone who seeks a career in the digital space.

Kezia O. Owusu-Ankomah,

Digital Marketer

I wish I was 18 when I saw ReadyforWork digital career accelerator. I've been in the media and arts industry for 12 years. And I developed a new interest in digital marketing. The best platform I found was ReadyforWork. I learned to believe in myself. I also learned how to use design thinking to drive innovation and essential social media marketing skills to drive sales, enhance audience engagement and build a community around a brand. If you are a young person looking to develop a new set of skills or want to complement your degree or practice, I recommend ReadyforWork digital career accelerator.

Diana Osei,

UX/UI Researcher

"INVIGORATING! That is how I will sum up my ReadyforWork digital career accelerator program experience. Through the coaching sessions, curriculum and deliverables, I gained confidence in my ability to provide strategic direction for a company's products and services from a User Experience point of view."

Prince Dogbe,

Analyst, GFA Consulting

SFAN gave me the greatest opportunity of my life so far, and that is my current job as a Senior Analyst at the Financial Advisory unit of GFA Consulting Ltd. I am grateful to the SFAN team for the ReadyforWork program and will happily recommend it to all.