Data Analytics Training
Our Data Analytics Training is designed to equip learners with the skills and tools required to analyze, interpret, and visualize data for effective decision-making in various industries. The program covers data collection, cleaning, analysis, visualization, and reporting using a range of industry-standard tools.
Key Components of the Training:
1. Introduction to Data Analytics
- Understanding the role of data in decision-making.
- Types of data analytics: Descriptive, Diagnostic, Predictive, and Prescriptive.
- Data lifecycle and fundamentals of data-driven decision-making.
2. Microsoft Excel for Data Analysis
- Data entry, sorting, filtering, and formatting.
- Advanced formulas and functions (VLOOKUP, INDEX-MATCH, IF statements, PivotTables, etc.).
- Data visualization using charts, graphs, and dashboards.
- Introduction to Power Query for automation.
3. SQL (Structured Query Language) – Database Management & Analysis
- Introduction to relational databases and SQL fundamentals.
- Writing basic and advanced SQL queries (SELECT, WHERE, GROUP BY, JOIN, UNION, etc.).
- Data extraction, filtering, and transformation using SQL.
- Working with database management systems like MySQL, PostgreSQL, and Microsoft SQL Server.
4. Python for Data Analytics
- Basics of Python programming and scripting.
- Libraries for data analysis: Pandas, NumPy, Matplotlib, Seaborn.
- Data wrangling and manipulation techniques.
- Exploratory Data Analysis (EDA) using Python.
- Building simple machine learning models with scikit-learn.
5. R Programming for Statistical Analysis
- Introduction to R and RStudio for statistical computing.
- Data manipulation with dplyr and visualization with ggplot2.
- Hypothesis testing, correlation, and regression analysis.
- Handling large datasets for data-driven research and reporting.
6. Power BI – Business Intelligence & Dashboarding
- Introduction to Power BI and its components.
- Connecting to data sources and data transformation using Power Query.
- Creating interactive dashboards and reports.
- Using DAX (Data Analysis Expressions) for advanced calculations.
- Sharing reports and collaborating with Power BI Service.
7. Tableau – Data Visualization & Reporting
- Understanding Tableau Desktop for visual analytics.
- Data connection and preparation for visualization.
- Creating interactive dashboards and storytelling with data.
- Working with calculated fields, filters, and parameters.
- Publishing and sharing reports via Tableau Public or Server.
8. SPSS – Statistical Data Analysis
- Introduction to SPSS (Statistical Package for Social Sciences).
- Importing and managing data in SPSS.
- Running descriptive statistics, correlation, and regression analysis.
- Hypothesis testing (ANOVA, Chi-square, T-tests).
- Generating statistical reports for academic and business research.
9. Data Analytics Capstone Project
A real-world project where learners apply the skills they have acquired.
- Data cleaning, analysis, and visualization using multiple tools.
- Interpretation of results and data storytelling.
- Presentation of findings through dashboards and reports.
10. Career Support & Certification
Resume building and LinkedIn profile optimization for data analytics roles.
Mock interviews and preparation for data analyst job interviews.
Guidance on acquiring industry certifications like Microsoft Certified Data Analyst, Tableau Desktop Specialist, Google Data Analytics Certificate, etc..
This comprehensive Data Analytics Training ensures learners are equipped with the right skills to work in diverse industries, including finance, healthcare, business intelligence, research, and marketing analytics.
Course Fee
Online Class
beginner (3 months) --> N50,000.00
Advance (6 months) --> N90,000.00
Apply Now
Physical Class
beginner (3 months) --> N150,000.00
Advance (6 months) --> N250,000.00
Apply Now