Complete Data Analyst Bootcamp From Basics To Advanced
Ready to transform raw numbers into meaningful insights that shape smarter decisions and business growth? At Nepthink Solutions, our practical Data Analysis Training equips you with the essential tools, techniques, and industry experience you need to interpret data and solve real-world problems using Excel, SQL, Power BI, and Python.
Data Analysis is one of the most in-demand and rewarding skills across industries today. From banking to healthcare, e-commerce to technology, organizations need professionals who can analyze trends, forecast outcomes, and guide strategic decisions. This course gives you the expertise to stand out in today’s data-driven job market.
Our Port Harcourt-based Data Analysis course is designed for beginners, business professionals, developers, and analysts who want to sharpen their analytical skills. With a project-focused curriculum, you’ll build a professional portfolio by working on real-world datasets that mirror the challenges faced by top companies.
You’ll learn directly from experienced analysts and industry experts as they mentor you through core topics such as data cleaning, visualization, reporting, dashboard creation, and statistical analysis. You’ll gain hands-on experience with tools like Excel, SQL, Tableau/Power BI, and Python—all while learning how to extract valuable insights and present data in ways that drive impact.
Join the Best Data Analysis Academy in Port Harcourt Today!
Searching for the most affordable and effective Data Analysis training in Port Harcourt? Nepthink Technologies delivers world-class training designed to prepare you for high-demand roles in business, tech, and beyond. Take the first step toward becoming a data-driven professional—start your journey with us today!
What You Will Learn
Section 1: Introduction to Data Analytics
- What is Data Analytics? Roles and Applications
- Types of Data Analytics: Descriptive, Diagnostic, Predictive, Prescriptive
- Setting Up Your Data Analytics Environment
- Introduction to Python, Excel, and SQL for Data Analysis
Section 2: Data Collection & Cleaning
- Data Sources: Databases, APIs, and Files
- Handling Missing and Duplicate Data
- Data Cleaning Best Practices
- Data Transformation & Preparation
Section 3: Exploratory Data Analysis (EDA)
- Understanding Data Distributions
- Summary Statistics & Basic Insights
- Identifying Outliers and Trends
- Feature Relationships and Correlations
Section 4: Data Visualization
- Charts and Graphs with Excel & Python
- Visualization with Matplotlib and Seaborn
- Interactive Dashboards with Power BI / Tableau
- Storytelling with Data Visuals
Section 5: Statistics for Data Analysis
- Descriptive and Inferential Statistics
- Probability Basics & Sampling Techniques
- Hypothesis Testing & Confidence Intervals
- Correlation vs Causation in Analysis
Section 6: Excel & SQL for Data Analysis
- Excel Functions for Data Analysis
- Pivot Tables & Data Summarization
- SQL Queries for Analysis (SELECT, JOIN, GROUP BY)
- Integrating SQL with Python/Excel
Section 7: Advanced Analytical Techniques
- Regression Analysis for Insights
- Time Series Analysis & Forecasting
- Segmentation and Cohort Analysis
- Basic Predictive Modeling for Analysts
Section 8: Business Intelligence & Reporting
- Designing Effective Dashboards
- Using Power BI and Tableau for Business Reports
- Automating Reports with Python & Excel
- Presenting Data to Stakeholders
Section 9: Real-World Projects
- Sales & Marketing Data Analysis
- Customer Segmentation & Retention
- Financial and Business Forecasting
- Capstone Project: End-to-End Data Analysis
Section 10: Ethics, Careers & Portfolio
- Data Privacy & Ethical Analysis
- Building a Data Analysis Portfolio
- Resume & LinkedIn Optimization
- Freelancing, Remote Work & Career Paths
Section 11: Graduation & Certification
- Final Assessment & Case Study Presentation
- Issuance of Certificate
Course Content:
- What is Data Analysis?
- Applications of Data Analysis
- Roles of a Data Analyst
- Types of Data Analysis (Descriptive, Diagnostic, Predictive, Prescriptive)
- Setting Up Tools (Excel, Python, SQL)
- Python Basics & Jupyter Notebook
- Working with Excel Functions
- Data Manipulation with Pandas & NumPy
- Excel Pivot Tables & Charts
- Integrating Python with Excel
- Importing Data (CSV, Excel, SQL, APIs)
- Handling Missing & Duplicate Data
- Dealing with Outliers
- Data Transformation Techniques
- Preparing Data for Analysis
- Understanding Data Distributions
- Descriptive Statistics & Insights
- Detecting Patterns & Trends
- Correlation & Relationships
- Case Study in EDA
- Visualization with Excel & Python
- Charts with Matplotlib & Seaborn
- Interactive Dashboards with Tableau/Power BI
- Visualization Best Practices
- Storytelling with Data
- Descriptive Statistics
- Probability Basics & Sampling
- Inferential Statistics
- Hypothesis Testing & Confidence Intervals
- Correlation vs Causation
- Introduction to Relational Databases
- Basic SQL Queries (SELECT, WHERE, JOIN)
- Aggregate Functions & Subqueries
- Using SQL with Python & Excel
- Data Extraction from APIs
- Designing Reports for Stakeholders
- Power BI Dashboards
- Tableau for Business Insights
- Automating Reports with Python/Excel
- Effective Data Storytelling
- Regression Analysis for Business Insights
- Segmentation & Cohort Analysis
- Time Series Forecasting
- Predictive Analytics for Decision-Making
- Case Studies in Data Analysis
- End-to-End Data Analysis Project
- Business & Sales Data Analysis
- Customer Segmentation Project
- Capstone Project
- Building a Portfolio
- Preparing for Data Analyst Interviews
- Resume & LinkedIn Optimization
- Freelancing & Remote Opportunities
- Mock Interviews & Feedback
- Certificate Issuance
