• info@comfortdevelopers.com
  • +234 806 742 1633
4.50
(2 Ratings)
Wishlist Share
Share Course
Page Link
Share On Social Media
Categories: Data Analysis

About Course

This course provides a comprehensive introduction to data analysis, equipping you with the tools and techniques to extract, process, and interpret data to make informed decisions. By the end of the course, you’ll be able to analyze datasets, uncover trends, and communicate insights effectively.

What Will You Learn?

  • Introduction to Data Analysis
  • Understand the fundamentals of data analysis, including the process of collecting, cleaning, and interpreting data.
  • Learn the different types of data (qualitative vs quantitative) and their role in analysis.
  • Data Collection and Data Sources
  • Learn how to gather data from various sources such as databases, spreadsheets, and external sources like APIs.
  • Understand the importance of data quality and consistency in the analysis process.
  • Data Cleaning and Preparation
  • Master techniques for cleaning raw data, including handling missing values, correcting errors, and standardizing data formats.
  • Learn how to preprocess data to make it ready for analysis.
  • Exploratory Data Analysis (EDA)
  • Learn how to explore data to identify trends, patterns, and outliers using statistical methods and visualizations.
  • Discover how to use tools like Python (with libraries such as Pandas and Matplotlib), R, Excel, or Power BI for EDA.
  • Data Visualization
  • Understand the importance of visualizing data to uncover insights and communicate findings effectively.
  • Learn how to create and interpret various types of charts, graphs, and dashboards using tools like Excel, Tableau, or Power BI.
  • Statistical Analysis
  • Learn the basics of statistics, including measures of central tendency (mean, median, mode), dispersion (variance, standard deviation), and correlation.
  • Understand how to perform hypothesis testing, correlation analysis, and regression analysis.
  • Data Modeling and Predictions
  • Learn about predictive modeling techniques such as linear regression, decision trees, and machine learning algorithms.
  • Understand how to apply these models to make data-driven predictions and decisions.
  • Data Interpretation and Reporting
  • Learn how to analyze and interpret data results to draw actionable insights.
  • Understand how to present data findings in a clear and concise manner for stakeholders through reports or presentations.
  • Advanced Data Analysis Techniques
  • Explore advanced techniques such as time series analysis, clustering, and classification.
  • Learn how to analyze complex datasets to uncover deeper insights.
  • Data Analysis Tools
  • Gain proficiency in popular data analysis tools like Excel, Python (with Pandas, NumPy, and Scikit-Learn), R, Power BI, and Tableau.
  • Understand how to choose the right tool for different types of data analysis tasks.
  • Data Ethics and Privacy
  • Understand the ethical considerations involved in data analysis, including data privacy, transparency, and the responsible use of data.
  • Problem-Solving with Data
  • Learn how to apply data analysis techniques to solve real-world problems in areas like business, marketing, healthcare, finance, or social sciences.

Course Content

PYTHON ENVIRONMENTAL SETUP
This course is your guide to setting up a robust and efficient Python development environment. You'll learn the essential steps to install Python, configure tools, and create an optimal setup for smooth coding and project management.

  • INTRODUCTION TO PYTHON
    00:42
  • WHAT IS PHYTHON
    05:17
  • JUPYTER NOTEBOOK
    01:21
  • INSTALLING JUPYTER NOTEBOOK
    06:46
  • RUNNING JUPYTER NOTEBOOK
    08:45
  • COMMON JUPYTER NOTEBOOK
    07:29
  • JUPYTER NOTEBOOK COMPONENT
    04:27
  • JUPYTER NOTEBOOK DASHBOARD
    04:21
  • NOTEBOOK INTERFACE
    05:45

DATA ANALYSIS WITH PYTHON
This course provides a hands-on introduction to data analysis using Python, one of the most powerful and versatile programming languages for data science. Through practical examples, you’ll learn how to clean, manipulate, visualize, and analyze data, preparing you to tackle real-world data problems efficiently. By the end of this course, you'll be proficient in using Python's key libraries to perform data analysis tasks.

DATA ANALYSIS WITH POWER BI
Power BI is a powerful business intelligence tool that enables data analysts and professionals to transform raw data into actionable insights through interactive reports and dashboards. This course will teach you how to effectively use Power BI for data analysis, from importing data to creating complex visualizations and reports. You will learn how to analyze and present data in an intuitive and visually compelling manner, helping stakeholders make data-driven decisions.

DATA ANALYSIS WITH EXCEL
This course is designed to help you master the art of data analysis using Microsoft Excel, one of the most powerful and widely used tools for analyzing and visualizing data. Whether you are a beginner or have some experience, this course will guide you through the key features and techniques in Excel to make data-driven decisions and uncover valuable insights.

DATA ANALYSIS WITH TABLEAU
This course provides hands-on training in using Tableau, a leading data visualization and business intelligence tool, to perform powerful data analysis. Learn how to connect, prepare, and visualize data to create insightful dashboards and reports that drive informed decision-making.

Student Ratings & Reviews

4.5
Total 2 Ratings
5
1 Rating
4
1 Rating
3
0 Rating
2
0 Rating
1
0 Rating
3 years ago
I truly enjoyed this class and really liked the student-professor interaction. ... The more I learn today, the less risky moves I will make in the future.
3 years ago
Excellent course! Educators are knowledgeable and thoroughly enjoy the topic creating a fun laid-back learning atmosphere. Will take more courses