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?

Introduction to Data Science

This session will introduce participants to Data Science. Some use cases, and an overview of its landscape (Open source software, infrastructure, databases, tools...) will be presented.

Introduction to Probability & Statistic + Explanratory Data Analysis (EDA)

A solid background on probability and statistics is essentially in analyzing and generating insights from data.

Regression, Classification Techniques & Dimension Reduction

Overview of techniques in data analysis such as regression, and clssification will be presented. Knowing when to use an approach is essential for a data scientist.

Data Mannipulation, Wrangling and Data Visualization in R

Accessing data reliably, and preparing it for use is very common in data science. This session will include Getting Data, Connecting R to database management systems, Profiling, Data Wrangling, Visualization.

Time Series Analysis

It is common to encounter time series datasets in real world problems. This session will provide an introduction to analyzing such datasets.

Intro to Statistical Learning: Supervised Learning

The Lectures on Statistical (or Machine) Learning will include: Decision Trees (Classification and Regression Tree, Random Forest, ....) , Recommender Systems, Boosting, Reinforcement Learning, Anomaly Detection, Natural Language Processing (Topic Modelling, Sentiment Analysis, Word Embedding,...), Neural Network, Convolutional Neural Network, Recurrent Neural Network,

Communication of results & how to build smart interactive apps.

How results are communicated is a must-have skill for data science practitioners.

Presentations of Data Science Project works by Students

This session will provide a space for students to present their data science project assignment.

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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

6 Weeks Coursework

Experience

Entry-Level
Mid-career 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

Peter Addo

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.