Unleash Your Potential: Discover Opportunities in Data Science
Data science is the field of discovery, interpretation, and communication of meaningful patterns in data. At the heart of this dynamic and exciting field is the data scientist, armed with an arsenal of scientific methods, algorithms, and systems to extract valuable insights from both structured and unstructured data. Whether you're looking to become a data analyst, data engineer, data architect, business analyst, or machine learning expert, the possibilities for a fulfilling and rewarding career in data science are virtually endless. Join the ranks of the data science elite and start making a real impact in your organization today!
Duration
2 Months
Learning Options:
On-Campus
Course Fee
₦200,000 NGN
Prerequisite
Computing & Math knowledge
Next Start Date
1st April 2024
Certification
AfriHUB Data Scientist
Course Outline
Introduction to Data Science and Tools
This module provides an introduction to data science and essential tools, including Python, Pandas, Scikit-learn, NumPy, Keras, and more. Participants will gain a foundational understanding of the tools required for data analysis and modeling..
Statistics and Data Visualization
This module combines statistics and data visualization. It covers statistical topics such as sampling, probability distributions, descriptive statistics, correlation, and hypothesis testing. Participants will also learn how to create captivating data visualizations using Seaborn, Matplotlib, and Plotly.
Dashboard Design and Practical Application
This module focuses on designing interactive dashboards using Google Data Studio or Microsoft PowerBI. Participants will apply their skills by working on real-world data analysis and statistical case studies.
Machine Learning and Predictive Modeling
In this module, participants delve into machine learning theory, covering regression, decision trees, random forests, K-nearest neighbors, support vector machines, and more. They will learn how to build and evaluate predictive models.
Data Science in Specific Domains
This module explores data science applications in marketing and retail. It covers modeling engagement rates, A/B testing in marketing, and customer segmentation, lifetime value, and product analytics in retail.
Big Data and PySpark
This module addresses big data challenges, including Hadoop, MapReduce, Spark, and PySpark. Participants will learn about RDDs, data transformations, actions, and machine learning with PySpark (MLlib). Data cleaning and manipulation at scale are also covered.