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Since March 2023
Instructor since March 2023
TRAINING IN POWER BI , Business Intelligence, DAX, Power Query, Dashboards, Data Analytics, Data Visualisation, Microsoft Power BI, and Busi
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From 89 C$ /h
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Master Microsoft Power BI – From Beginner to Advanced Data Analytics

Unlock the power of data with Microsoft Power BI and learn how to transform raw information into meaningful insights and interactive dashboards. Whether you are a complete beginner, a university student, or a working professional looking to improve your analytical skills, this course will equip you with the practical knowledge needed to analyse data with confidence.

As an experienced university lecturer and business analytics tutor, I provide hands-on, project-based lessons that focus on real-world applications rather than theory alone. Every session is tailored to your experience level and learning objectives.

What you will learn
Introduction to Microsoft Power BI Desktop
Connecting to multiple data sources (Excel, CSV, SQL databases, SharePoint, and online services)
Data cleaning and transformation using Power Query
Data modelling and relationships
Creating interactive reports and professional dashboards
DAX (Data Analysis Expressions) fundamentals and advanced calculations
Charts, maps, KPIs, slicers, and custom visualisations
Drill-through, bookmarks, and report navigation
Publishing reports to the Power BI Service
Sharing dashboards and collaborating securely
Best practices for business intelligence and data storytelling
Why choose this course?
Learn through practical, real-world business scenarios.
Build professional dashboards from scratch.
Receive personalised guidance based on your goals and experience.
Develop skills that are highly valued by employers across finance, healthcare, business, marketing, operations, and data analytics.
Improve your confidence in analysing, visualising, and presenting data effectively.
Who is this course for?
Beginners with no previous Power BI experience.
University and college students.
Business professionals and managers.
Finance, accounting, HR, marketing, and operations professionals.
Data analysts and aspiring Business Intelligence (BI) professionals.
Anyone looking to develop in-demand data analytics skills.
Lesson Format

Lessons are available online and combine guided instruction, hands-on exercises, practical projects, and continuous feedback. By the end of the course, you will be able to create professional dashboards, automate reporting processes, and make data-driven decisions with confidence.

Whether you are preparing for a new career, enhancing your professional skills, or working on a university or business project, this course will give you the practical Power BI expertise needed to succeed.
Location
location type icon
Online from United Kingdom
About Me
I have been involved in the academia for my entire career. This enabled me to study a variety of subjects; among these are Micro economics, Macro economics, General Management and Communication, Project Management and Strategic Management before identifying my passion for the field of Entrepreneurship and Innovation Management. This has become my area of expertise as I have obtained my MBA (Developing Entrepreneurial Skills Among Students Through Entrepreneurship Development Program for Colleges – A Botswana perspective) cum laude and in December 2015 I have obtained my PhD with the title: “Women entrepreneurship in Botswana: characteristics of their enterprises and contributions to economic development”.
Education
PhD Business Management (Entrepreneurship)
(University of South Africa 2022)

Women entrepreneurship in Botswana: characteristics of their enterprises and contributions to economic development

Executive Master of Business Administration degree (7.38 GPA) (First Class)
(AMITY University 2015)

Developing Entrepreneurial Skills Among Students Through Entrepreneurship Development Program for Colleges – A Botswana perspective.

B.Com. Economics degree
(University of South Africa 2007)
Experience / Qualifications
Khulekani is a holder of an Ph. D in Management Studies an MBA in Business Management, a Bachelor of Commerce degree in Economics, awarded by the University of South Africa in 2007. The focus of my MBA thesis was on Developing Entrepreneurial Skills Among Students Through Entrepreneurship Development Program for Colleges. Khulekani enrolled for a Ph.D. in Management studies at the University of South Africa, in 2017.
He oversees the management of GIPS University College in Botswana as an academic manager and Senate academic chair. He has twelve (12) years of lecturing experience at the undergraduate level in Business Management. Entrepreneurship,Economics, Small Business Management, Entrepreneurship and Development, Research Report and Business Statistics, Analytical Decision Making, and Entrepreneurship are some of the courses he has delivered. In addition, he has previously served as a research supervisor for undergraduate students. A total of over thirty honors research projects have been successfully completed under his tutelage. He's a researcher who does research in several fields of study. Among the many topics, he researches include entrepreneurship, in which he examines every stage of a company's lifecycle, from conception to exit. Among his special interests are women and student entrepreneurship, to name only two examples of his work in both fields. There are specific issues that women-owned businesses face, which he looks at in order to uncover how the family and business domains are intertwined, both for and against the interests of these women entrepreneurs, in order to provide solutions based on empirical evidence for addressing the problems and capitalizing on opportunities. He is especially interested in how students can transcend from merely having business ideas to really acting on those ideas and transforming them into a genuine firm.
Age
Children (7-12 years old)
Teenagers (13-17 years old)
Adults (18-64 years old)
Seniors (65+ years old)
Student level
Beginner
Intermediate
Advanced
Duration
60 minutes
The class is taught in
English
Availability of a typical week
(GMT -04:00)
New York
at teacher icon
Online via webcam
Mon
Tue
Wed
Thu
Fri
Sat
Sun
00-04
04-08
08-12
12-16
16-20
20-24
This class provides comprehensive assignment assistance tailored to the unique needs of students at the undergraduate, master’s, and Ph.D. levels. Designed to enhance academic performance, it offers personalized support in research, writing, and problem-solving across a variety of disciplines.

Key Features of the Class:
1. Undergraduate Support:
• Assistance with essays, reports, and case studies.
• Guidance on foundational research and citation techniques.
• Help with understanding key concepts and coursework requirements.
2. Masters-Level Support:
• Advanced guidance for research papers, literature reviews, and presentations.
• Assistance with thesis development and structured writing.
• Support for critical analysis and advanced academic formatting.
3. Ph.D.-Level Support:
• Expert mentoring in creating and refining dissertations.
• Assistance with developing research proposals and methodologies.
• Support with peer-reviewed journal articles and advanced data analysis.

Learning Outcomes:
• Gain confidence in completing assignments to a high academic standard.
• Develop stronger research, writing, and analytical skills.
• Improve understanding of academic expectations at different levels of study.

This class is ideal for students seeking structured guidance and expert insights to achieve academic excellence at any stage of their educational journey.
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Course Description:

The BTEC Business and Enterprise course offers a comprehensive exploration into the dynamic world of business, equipping students with the essential knowledge and skills to thrive in various entrepreneurial endeavors. Through a blend of theoretical learning and practical application, students will delve into key concepts, strategies, and techniques vital for success in the modern business landscape.

This course covers a wide array of topics, including:

Business Fundamentals: Students will gain a solid understanding of fundamental business concepts such as business aims and objectives, stakeholders, business structures, and the role of business in society.

Marketing and Promotion: Explore the principles of marketing and promotion, including market research, segmentation, targeting, branding, advertising, and digital marketing strategies.

Financial Management: Learn about financial statements, budgeting, costing, pricing strategies, profit maximization, and financial performance analysis.

Entrepreneurship: Delve into the mindset and skills required to succeed as an entrepreneur, covering areas such as opportunity recognition, business planning, risk management, innovation, and creativity.

Operations Management: Understand the importance of efficient operations management, including production processes, supply chain management, quality control, and lean principles.

Human Resources: Explore the role of human resources in business, including recruitment, training, motivation, leadership, and organizational culture.

Throughout the course, students will engage in practical activities, case studies, and real-world projects to apply theoretical concepts to practical situations, fostering critical thinking, problem-solving, communication, and teamwork skills. Emphasis will be placed on developing entrepreneurial mindsets and fostering innovation, preparing students for diverse career paths in business, management, or entrepreneurship.

Assessment will be varied, including assignments, presentations, case studies, and practical projects, enabling students to demonstrate their understanding and skills in a range of contexts. By the end of the course, students will emerge with a well-rounded understanding of business and enterprise, ready to embark on further education or pursue careers in the dynamic world of business.
Read more
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1-1 What is data mining, its procedures and tools
1-2 What type of data is mined?
1-3 What are databases?
1-4 Relational Database
1-5 Query Language
1-6 Benefits of Database Mining
1-7 months data mining applications
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2-2 Statistical Description of Data
2-3 Visualization of Data
2-4 Measuring data similarity and difference
Chapter Three: Preparing Data for Analysis and Mining
3-1 The importance of preparing data for analysis and mining
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3-3 Data Integration
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3-5 Data Transformation and Data Individualization

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5-2 Classification using decision tree extrapolation
5-3 Classification using probability theory (hypothetical theory)
5-4 Classification using hypothetical network theory
5-5 Classification using correlation rules extrapolation
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5-7 Classification using the nearest neighbor algorithm
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6-5 High-Dimensional Clustering
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1-6 Benefits of Database Mining
1-7 months data mining applications
A - Business Intelligence (Business Intelligence)
B - Internet search engines

Chapter Two: Data Recognition
2-1 Data Types, Characteristics, and Features
2-2 Statistical Description of Data
2-3 Visualization of Data
2-4 Measuring data similarity and difference
Chapter Three: Preparing Data for Analysis and Mining
3-1 The importance of preparing data for analysis and mining
3-2 Data Cleanup
3-3 Data Integration
3-4 Data Reduction
3-5 Data Transformation and Data Individualization

Chapter Four: Pattern Discovery and Exploration, Dependency and Correlation Rules
4-1 Basic Concepts
4-2 Shopping basket analysis (example)
4-3 Evaluating the dependency and correlation rules being explored
4-4 Mining Multi-Level Dependency and Linkage Rules
4-5 Mining multidimensional dependency and correlation rules
4-6 Rules of nominal and quantitative dependency and correlation
4-7 Exploring and identifying rare and negative patterns
4-8 Exploring and Determining the Rules of Dependency and Conditional Linkage
4-9 Evaluating dependency and correlation rules and distinguishing between useful and unhelpful ones
4-10 Measuring the type and strength of the relationship in dependency and correlation rules
4-11 Applications of pattern mining in practical life

Chapter Five: Analysis and Mining Using Classification and Prediction Algorithms
5-1 Basic Concepts
5-2 Classification using decision tree extrapolation
5-3 Classification using probability theory (hypothetical theory)
5-4 Classification using hypothetical network theory
5-5 Classification using correlation rules extrapolation
5-6 Classification using neural network algorithm
5-7 Classification using the nearest neighbor algorithm
5-8 Multi-category classification algorithms
5-9 Evaluating the efficiency and selection of classification algorithms

Chapter Six: Analysis and Mining Using Cluster Hashing Algorithms
6-1 Basic Concepts
6-2 Clustering by Division
6-3 Hierarchical Clustering
A. Hierarchical clustering
b. Hierarchical fission
6-4 Probability Clustering
6-5 High-Dimensional Clustering
6-6 Clustering of graphs and network data
6-7 Conditional Clustering
6-8 Cluster Segmentation Assessment

Chapter Seven: Analyzing and Mining Outliers and Complex Data Types
7-1 Basic Concepts
7-2 Types of extreme values
7-3 Ways to Explore Extreme Values
7-4 Complex Data Analysis and Mining

Chapter Eight: Planning Data Mining Operations and Their Applications in Society
8-1 Planning Data Mining Operations
8-2 Data Mining in the Community
8-3 Data mining applications in vital areas of society
8-4 Practical Application: Recommendation System Usage Scenario

Appendix 1: Database Fundamentals
Appendix 2: Data Warehouse Fundamentals
Appendix 3: Glossary of Data Mining Terms
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Soy Ingeniera Informática por la Universidad Carlos III de Madrid y trabajo como Data Engineer, construyendo plataformas de datos en la nube con Snowflake y Azure. En mis clases aprenderás lo que de verdad se usa en el mundo profesional, explicado de forma clara y práctica.

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