Data Analysis

This course provides a comprehensive introduction to data analysis, equipping learners with the essential skills to extract insights, interpret data, and drive decision-making using statistical and analytical tools. Participants will gain hands-on experience with industry-standard technologies, including SQL, Excel, Python, and Business Intelligence (BI) tools, to analyze and visualize data effectively. By the end of this course, learners will be proficient in data manipulation, trend analysis, and predictive modeling, enabling them to make data-driven business decisions.

What You Will Learn

Data Visualization & Interpretation

Creating compelling data visualizations using Tableau, Power BI, and Matplotlib
Understanding dashboards, reports, and key performance indicators (KPIs)
Best practices for effective storytelling with data

SQL for Data Analysis

Writing SQL queries to retrieve, filter, and aggregate data
Joins, subqueries, and advanced SQL functions for data manipulation
Database management and optimization techniques

Excel for Data Analytics

Data cleaning, transformation, and analysis using pivot tables, charts, and formulas
Introduction to Power Query and Power Pivot for advanced reporting
Automation using Excel Macros (VBA)

Python for Data Analysis & Machine Learning

Data manipulation with Pandas and NumPy
Statistical analysis and hypothesis testing with SciPy and Statsmodels
Machine learning basics with Scikit-learn

Business Intelligence (BI) & Decision-Making

Implementing ETL (Extract, Transform, Load) processes
Understanding BI workflows and real-time reporting solutions
Applying analytics for business growth and competitive advantage

Real-World Projects & Case Studies

Hands-on data analysis projects in finance, healthcare, e-commerce, and marketing
Using big data techniques to process large datasets efficiently
Applying statistical and predictive analytics for real-world decision-making

This course is ideal for professionals in business, finance, marketing, IT, and anyone looking to build data analytics skills to enhance their career prospects.

Would you like this course to be tailored for a specific industry or integrate certification tracks like Google Data Analytics, Microsoft Power BI, or AWS Data Analytics?

Our Tech Pipeline:

Hands-on exercises, live projects, and industry case studies.
Introductory Training (Week 1-2)
Mentoring and Coaching (Week 3-10)
Practical Live and Workplace Skills (Week 3-10)
Work Experience via Live Projects and Business Cases (Week 3-10)
CV Review and LinkedIn Optimization
Job Search and Interview Preparation
On the Job Support (1 month)
Training Career Path: Data Analyst, Business Intelligence Analyst, Data Scientist.
Cost: $1000