Masterclass in Data Science and Business Analytics Course

Why select this training course?

Business analytics studies business data to gain insights and better decisions. Data scientists use data analytics to turn large volumes of data into actionable insights. Both of these roles require in-depth knowledge of statistics and database programming languages. They also require a strong understanding of data and how it relates to the business. Business analytics is the intersection of data and business. This field is growing rapidly as companies realize that having the correct data is not enough – they also have to know how to make the best use of it. The best business analysts and data scientists can understand the company’s goals and then work to find innovative ways to meet those goals using data.

How does data science differ from business analytics?

Business analytics is data-driven and focuses on business-related questions. It uses data analysis techniques to improve business functions. On the other hand, Data Science involves gathering, modeling and analyzing data. Because of this, many organizations have begun to invest in data science and analytics. They turn data into information that business leaders can use to improve business functions and make better decisions.

Over the past several years, the pace of digitization has grown rapidly. This has caused a spike in demand for data science solutions globally. Corporations are hiring data scientists and other data-related professionals to integrate data science solutions into their daily operations. The growth of digitization has created new opportunities for businesses to use data to improve their operations and provide better customer service.

How will a course in data science and business analytics help budding professionals?

Recognizing this industry’s need, Rcademy has introduced Masterclass in Data Science and Business Analytics Course. Whether you’re a working data scientist or a recent college graduate hoping to break into the field, this course will teach you the skills and knowledge you need to succeed. Rcademy understands Data Science has become an essential skill for finding solutions to a wide range of challenging business problems; therefore, it focuses on applying data-driven methods and techniques to various problems. Sign up for the course and gain an answer to questions such as how data science can reduce costs in the business. How can a business analytics culture be built in the company? How can business analytics improve decision-making? Etc.

Master data science by learning from industry experts. Gain real-world experience in data science by taking our comprehensive training course, curated by working data scientists and experts. Dive deep into data, learn cutting-edge techniques, and build real-world applications with our instructor-led classroom and online workshops. Develop a strong foundation in data science and analytics fundamentals by harnessing the power of data and building industry-relevant skills.

Who should attend?

The Masterclass in Data Science and Business Analytics Course by Rcademy is for any participant interested in the field of data science and analytics:

• Data managers
• Business analysts
• Graduates and Scholars
• IT professionals
• Project managers
• Entrepreneurs
• Quality Analysts

What are the course objectives?

The Masterclass in Data Science and Business Analytics Course by Rcademy has been designed the course revolving around the following objectives:

• Understand the fundamentals of data science and business analytics as well as their interrelationship
• Develop practical and professional competence in the field
• Learn to make strategic decisions in a broad range of business-related situations
• Learn the application of what you have learned in a professional environment
• Learn to analyze data, design and build data-driven business solutions, and communicate effectively about data-related issues
• Learn to approach data-related challenges from a variety of angles and use the right tools for the job
• Develop the perspective to frame the business problem of a statement by setting and testing hypotheses for key business issues
• Learn to discover patterns and trends in business data
• Develop the skills of logical reasoning, and critical thinking useful in business analytics
• Develop the useful skill of data visualization and storytelling to influence the targeted audience

How will this course be presented?

• Interactive sessions
• Use of case studies
• Management games
• Learning preparation of reports, charts, graphs
• Real-time exercises
• Problem-solving and Group discussion sessions

What are the topics covered in this course?

Module 1: Introduction to Data Science

• Fundamentals of data science
• Understanding the Big Data
• Descriptive statistics
• Setting and testing of hypothesis
• Use of data science in marketing and finance
• Data warehousing

Module 2: Understanding Business Analytics

• Customer analytics and dashboard
• Risk Analytics
• Data Science Vs. Business Analytics
• Business Intelligence
• Detective Analysis

Module 3: Techniques of Data Science

• Advanced statistics: Analysis of Variance, regression analysis
• Dimension reduction techniques
• Data mining
• Text mining
• Supervised and unsupervised learning

Module 4: Forecasting techniques

• Predictive modeling
• Time series forecasting
• Machine learning techniques
• SQL programming
• Optimization techniques: liner programming, goal programming

Module 5: Data Exploration

• Data discovery vs data exploration
• Data exploration as part of advanced analytics
• Steps in data exploration: goal setting, method selection and visualization
• Qualitative and quantitative methods of data exploration

Module 6: Data Visualisation

• Visualization tools: charts
• Creating performance dashboards
• Visual Analytics
• Design principles

Module 7: Business Problem Framing

• Formulation of a statement of the problem
• Formulating hypothesis
• Transformative problem formulation
• Defining dependent variable

Module 8: Predictive Modelling 

• Prediction vs Interpretation
• Data transformation
• Classification model
• Clustering model
• Outliers model

Module 9: Data Analysis in Excel

• Adding data to Excel
• Sorting, filtering
• Conditional formatting
• What-if Analysis
• Pivot Tables

Module 10: Future Trends

• Augmented Analytics
• Data cleaning
• Automation of Machine Learning
• Data quality management
• Use of cloud
• Cognitive analytics

Module 11: Application of Data Science and Business Analytics in Different Industries

• Business Analytics in Financial Services
• Business Analytics in Customer Relationship and marketing management
• Data Science in Information Technology