data science

This is a 2-day end-to-end training on business analytics for all professionals, including those with no prior analytics experience. You’ll learn how data analysts describe, predict, and inform business decisions in the specific areas of marketing, human resources, finance, and operations, and you’ll develop day-to-day basic data literacy and an analytic mindset that will help you make strategic decisions with the use of robust data. At the end of the course, you will be provided with data which will need your hands-on application of the skills learned to interpret a real-world data set and make appropriate strategic business recommendations.

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At this workshop, it’s assumed that you have little or no understanding of the following:

Business Intelligence (BI)

Database and Data-Warehousing (DB and DW)

Business Analytics (Prescriptive, Descriptive and Predictive)

Big Data (Sentiment Analysis)

Data Science

To practically and effectively learn in this class, we require that you come along with a working laptop with minimum specification of 4GB RAM, 500GB HDD.

Week 1 (March 16, 2019)

Concept of Business Intelligence

  • Description of Business Intelligence concept for Business use
  • Simple architecture of an EDW
  • Data mart and its attributes
  • ERD
  • Introduction to Data Modeling
  • Introduction to Facts and Dimensions

Data Visualization

  • Introduction to Tools and Terminology
  • Dashboard in Minutes
  • Excel vs Power BI
  • Setup and manage relationships
  • Creating calculated columns
  • Creating measures
  • Map Visualizations
  • Custom visuals
  • Drill Down/Up
  • Hierarchies
  • Publishing and sharing visualizations
  • Exporting data from a visualization
  • Custom Q&A questions
  • Transform data into actionable insights

Week 2 (March 23, 2019)

Business Analytics concept

  • Introduction to Descriptive Analytics
  • Introduction to Prescriptive Analytics
  • Introduction to Predictive Analytics
  • Market basket analysis
  • Classification
  • Regression
  • Segmentation

Big Data Concept

  • Introduction to Big Data
  • Big Data Technologies
  • Sentiment analysis

Introduction to Data Science (Using R and Python)

  • Introduction to R and Python for Data Science
  • Vectors, Matrices, Factors, Data frames, Lists
  • Data Pre-Processing

What to Expect

Gain understanding of business analytics with the use of robust data and the ability to take into account the relationships between this discipline and other areas of business to make holistic judgments when analyzing business situations.

Apply quantitative modeling and data analysis techniques to the solution of real world business problems, communicate findings, and effectively present results using data visualization techniques.

Apply ethical practices in everyday business activities and make well-reasoned ethical business and data management decisions.

Select, Prepare, Construct, Integrate, Structure, and Format data to be most effective to ensure the models meet the business goals.

Develop actionable plans from existing data and initiatives to increase sales, reduce marketing costs and improve customer retention.

Determine whether a piece of writing is positive, negative or neutral.

Demonstrate knowledge of statistical data analysis techniques utilized in business decision making.

Manage data efficiently and allow users to perform multiple tasks with ease.

how can we help you?

Contact us at Leadspace to book a co-working space, meeting room or other ancillary services .

Leadspace isn’t just your regular workplace. There’s something about the atmosphere or perhaps it’s the community, either way, it’s one of the coolest places to really work and get things done.

Oyinkansola Sadiq-Mabeko
Head of Content, Starta Advisory


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