What you will learn:
- Statistics Fundamentals: You’ll learn the fundamentals of statistics, including descriptive statistics, probability distributions, hypothesis testing, and regression analysis.
- Data Cleaning and Preprocessing: Data can often be messy and incomplete, so you’ll learn how to clean and preprocess data using tools like Python or R and libraries like Pandas, NumPy, and Scikit-learn.
- Data Visualization: You’ll learn how to visualize data using tools like Matplotlib, Seaborn, and Plotly to gain insights and communicate findings to others.
- Exploratory Data Analysis This involves using statistical and visualization tools to explore and analyze data, identify patterns, and gain insights into relationships between variables.
- Machine Learning: You’ll learn the basics of machine learning, including supervised and unsupervised learning, decision trees, random forests, k-nearest neighbors, and neural networks.
- Data Wrangling and Transformation: This involves transforming data from one format to another and performing operations like filtering, sorting, and merging data.
- Big Data Analysis: You’ll learn how to work with large datasets and distributed computing frameworks like Hadoop and Spark.
- Ethics and Bias in Data Analysis: This will cover ethical considerations and how to avoid bias when working with data, including issues like data privacy, fairness, and transparency.
In summary, a data analysis course would cover the fundamentals of data analysis, statistics, and machine learning, along with the necessary tools and techniques for working with data, manipulating and cleaning data, visualizing data, and gaining insights from it.
Capstone Project for all courses
For all courses, a capstone project As part of this course, you'll also work on a capstone project that will showcase your skills and expertise. This project will give you hands-on experience in analyzing a real-world dataset and presenting insights to stakeholders, which you can add to your portfolio to demonstrate your abilities to potential employers.
Early Bird Fee: N180,000
|Physical/Online||250,000||8 weeks (2 Months)|
Introduction to Data Analysis
Data Cleaning and Preprocessing
Data Visualization & Exploratory Data Analysis
Machine Learning & Data Wrangling and Transformation
Big Data Analysis & Ethics and Bias in Data Analysis
Get the Education You Need to Succeed in Data Analyst
Our course is designed to provide you with the skills and knowledge you need to become a proficient data analyst. Whether you're a beginner or have some experience in this field, our program is tailored to meet your needs.
Advantages of this training for you:
- Learning how to use statistical analysis to draw meaningful conclusions from data
- Mastering various data analysis tools and techniques, such as Excel, Python, and SQL
- Gaining a deep understanding of data visualization and presentation to effectively communicate insights to stakeholders
Become a lead generation across all data Analyst.
As part of this course, you’ll also work on a capstone project that will showcase your skills and expertise. This project will give you hands-on experience in analyzing a real-world dataset and presenting insights to stakeholders, which you can add to your portfolio to demonstrate your abilities to potential employers.
Don’t miss out on this opportunity to become a proficient data analyst.
Enroll in our Data Analysis course today and take the first step toward a rewarding career in the data analysis industry.