Browse our comprehensive course catalog featuring practical, career-ready data analysis skills
Our programs are structured to give you practical, career-ready data analysis skills. Each course is led by experts and incorporates real datasets so you can apply learning immediately.
From beginner to expert, covering descriptive analysis, advanced statistics, and modeling.
Master IBM SPSS Statistics from the ground up. Learn data entry, manipulation, and cleaning techniques. Progress through descriptive statistics, hypothesis testing, correlation analysis, regression modeling, and advanced statistical procedures. Includes hands-on practice with real datasets from health, education, and development sectors. Perfect for those who need to analyze survey data, conduct research, or work in monitoring and evaluation roles.
Flexible pace, small class sizes, work-study friendly.
Students, researchers, NGO staff, M&E officers.
Professional certificate in SPSS.
$500
Learning options: Individual Online (3 months) or Group Face-to-Face (1 week)
Training in data management, statistical analysis, and program evaluations.
Comprehensive STATA training for research and evaluation professionals. Learn data management, statistical analysis, and econometric modeling. Cover data import/export, variable creation, merging datasets, and advanced programming. Focus on program evaluation methods, impact assessment techniques, and policy analysis. Ideal for academic researchers, development professionals, and policy analysts working with large datasets.
45 hours spread across 3–6 months, depending on learner pace.
Researchers, graduate students, data analysts.
Certification in applied STATA for research and evaluations.
$500
Learning options: Individual Online (3 months) or Group Face-to-Face (1 week)
From coding basics to big data and machine learning.
Complete Python journey from basics to advanced data science and AI applications. Start with Python fundamentals, data structures, and control flow. Progress to data manipulation with Pandas, visualization with Matplotlib and Seaborn, and statistical analysis with NumPy and SciPy. Advanced topics include machine learning with Scikit-learn, deep learning basics, and big data processing. Work on real-world projects including predictive modeling, natural language processing, and computer vision applications.
Hands-on projects with real datasets.
Aspiring data scientists, professionals shifting into AI roles.
Certification in Python for Data Science.
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Learning options: Individual Online (3 months) or Group Face-to-Face (1 week)
Statistical modeling, regression, and advanced visualization.
Master R programming for advanced statistical analysis and data visualization. Learn data manipulation with dplyr and tidyr, statistical modeling with base R and specialized packages, and advanced visualization with ggplot2. Cover regression analysis, time series analysis, survival analysis, and multivariate statistics. Focus on reproducible research with R Markdown and version control. Perfect for researchers, statisticians, and analysts who need powerful statistical computing capabilities.
Practical exercises with open-source tools.
Analysts, researchers, advanced students.
Certification in R for advanced analytics.
$500
Learning options: Individual Online (3 months) or Group Face-to-Face (1 week)
Master Excel for data analysis, reporting, and visualization.
Comprehensive Excel training for data analysis. Learn advanced formulas, pivot tables, data visualization, and automation techniques. Progress through data cleaning, conditional formatting, chart creation, and dashboard development. Includes hands-on practice with business intelligence scenarios, financial analysis, and survey data processing. Perfect for professionals who need to analyze data efficiently without specialized software tools.
Flexible pace, hands-on practice with real datasets.
Students, researchers, business analysts, NGO staff.
Professional certificate in Excel Data Analysis.
$300
Learning options: Individual Online (3 months) or Group Face-to-Face (1 week)
Core principles of Monitoring, Evaluation, Accountability, and Learning (MEAL).
Comprehensive MEAL training covering the full project cycle from design to evaluation. Learn to develop logical frameworks, design monitoring systems, create data collection tools, and conduct evaluations. Cover quantitative and qualitative methods, participatory approaches, and stakeholder engagement. Focus on results-based management principles, theory of change development, and impact measurement. Includes practical exercises with real project examples from health, education, and development sectors.
3-month structured training.
Project managers, NGO staff, M&E specialists.
Certification in Results-Based Monitoring.
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Learning options: Individual Online (3 months) or Group Face-to-Face (1 week)
Join hundreds of learners who have transformed their careers with our comprehensive data analysis training programs.