Training In Key Business Intelligence Analyst And Data Science Training Course
Introduction
In today’s dynamic business environment, Business Intelligence and Data Science are crucial for driving organizational success and personal development. This Business Intelligence and Data Science Course combines essential analytical tools and skills to help you identify, explore, and address challenges using BI and data analytics. Participants will discover how sustainability-oriented innovation and real-world case studies can transform their organizations. Learn essential ideologies like systems thinking, multi-level perspectives, and multidisciplinary methods to tackle any obstacles. This BI and Data Analytics Training emphasizes critical skills such as teamwork, stakeholder cooperation, and responsible decision-making.
Course Highlights
- Real-World Applications: Engage with real-life business intelligence and data science examples.
- Data Visualization: Create impactful visual reports through data visualization training.
- Practical Exercises: Participate in hands-on exercises to deepen your understanding of data science and business intelligence.
- Comprehensive Support: Access course notes, materials, and ongoing support to enhance your learning experience.
- Empowerment: Develop the ability to independently analyze data and make data-driven decisions that improve business operations.
Master data mining and business intelligence, predictive analytics, big data analytics, and more, ensuring you stay at the forefront of industry trends.
How You Benefit
Upon completing this Business Intelligence Analyst and Data Science Course, participants will be able to:
- Data Mastery: Gather, organize, analyze, and visualize data effectively.
- Informed Decision-Making: Use data to enhance business decision-making processes.
- Metrics and Dashboards: Represent data through informational metrics, reports, dashboards, and KPIs.
- Comprehensive Analysis: Perform both quantitative and qualitative business analysis.
- Trend Analysis: Analyze current and historical data to discover trends, market conditions, and conduct competitor analysis.
- Data Fundamentals: Understand the basics of data leading to the science behind it.
- Practical Solutions: Solve real-world business analysis tasks with practical data science applications.
Who Should Attend
This Business Intelligence Analyst and Data Science Course is suitable for:
- Beginners: Those new to programming and data science.
- Career Enthusiasts: Individuals eager to pursue careers in business intelligence or data science.
- Resume Boosters: Applicants looking to enhance their resumes by applying knowledge to real-world issues.
- Programmers: Developers wanting to apply business reasoning to solve various problems.
- Career Pursuers: Anyone aiming for a career in Business Intelligence Analysis or Data Science.
Duration
10 Days
COURSE CONTENT
MODULE 1: BASICS OF INSIGHT GENERATION
- Data analytics is the new sliced bread
- Data value chain
- Tools for generating insights
- Business intelligence and data mining
MODULE 2: THE DIFFERENT DATA SCIENCE FIELDS
- Analysis vs analytics
- Why are there so many data science catchwords?
- Introduction to Business Analytics
- Introduction to Data Analytics
- Introduction to Data Science
- Introduction to Business Intelligence (BI), Machine Learning (ML), Artificial Intelligence (AI)
- BI vs. ML vs. AI – key characteristics and differences
MODULE 3: INTRODUCTION TO DATA AND DATA SCIENCE
- What is data science?
- History of data vs. information vs. data science
- What is the purpose of data science fields?
- Why do we need data science disciplines?
MODULE 4: COMMON DATA SCIENCE TECHNIQUES
- Traditional Data: Techniques
- Traditional Data: Real-life Examples
- Big Data: Techniques
- Big Data: Real-life Examples
- Business Intelligence (BI): Techniques
- Business Intelligence (BI): Real-life Examples
- Traditional Methods: Techniques
- Traditional Methods: Real-life Examples
- Machine Learning (ML): Techniques
- Machine Learning (ML): Types of Machine Learning
- Machine Learning (ML): Real-life Examples
MODULE 5: COMMON DATA SCIENCE TOOLS
- All the tools needed in business intelligence analytics and data science
- Data Science Jobs: what do they involve and what to look out for?
- Dispelling common misconceptions
- Population vs sample
MODULE 6: BASIC STATISTICS: FOUNDATIONS OF QUANTITATIVE INSIGHTS
- Basic statistics
- Types of variables
- Measures of central tendency
- Measures of dispersion
MODULE 7: THE NORMAL DISTRIBUTION AND HISTOGRAMS
- Normal distribution and histograms
- The empirical rule
- Covariance and correlation
MODULE 8: DATA VISUALISATION
- Data visualisation and Anscombe’s Quartet
- Data Cleaning using Tableau
- Bar chart and heat maps
MODULE 9: ADVANCED CHARTS AND DASHBOARDS
- Bar in bar graph and bullet graph visualisation
- Generating insights from social media data
- Dashboards
MODULE 10: DEMAND FORECASTING
- Regression analysis
- Demand forecasting
- Demand forecasting & smoothing methods
General Notes
- Expert Instruction: This course is delivered by seasoned trainers with vast experience in Business Intelligence Analyst and Data Science. The teaching approach combines practical activities, theory, group work, and case studies to ensure comprehensive learning.
- Materials Provided: Participants receive training manuals and additional reference materials to support their learning journey.
- Certification: Upon successful completion, participants are awarded a certification in Business Intelligence Analyst and Data Science.
- Customizable Training: We offer tailor-made courses to meet specific organizational needs. Contact us at training@skillsforafrica.org for more details.
- Location: Training takes place at the Skills for Africa Training Institute in Nairobi, Kenya.
- Inclusive Fees: The training fee includes tuition, materials, lunch, and venue. Accommodation and airport transfers can be arranged upon request.
- Payment Details: Payments should be sent to our bank account before the training starts, with proof of payment sent to training@skillsforafrica.org.