Simplilearn Business Analytics Course Review
Simplilearn’s Business Analytics Course is a training program designed to help individuals get a job and master the course of Business analytics. This course is customized for beginners and professionals who want to learn about business analytics.
Participants will learn how to work with various tools and software commonly used in the industry, including Excel, R, and Python. The course is structured to provide practical, hands-on experience through real-world projects and case studies. It’s a booming field so make sure to take part and prepare for the future.
But is it worth it??? Let’s know the reality here!
In this section, we shall be speaking about the complete details of the Simplilearn Business Analytics course and understand how it works. And what is Simplilearn Business Analytics Course Review
Duration also seems long here as for the Simplilearn Business Analytics Course Review, considering its a BootCamp.
Sure, here’s the simplified version in table format:
| Step | Column | Topics Covered |
|---|---|---|
| 1 | Business Analytics with Excel | Introduction to Business Analytics, Conditional Formatting and Essential Functions, Analysis with Pivot Tables, Dashboard Creation, Excel in Business Analytics, Statistical Data Analysis, Power BI |
| 2 | Database Management Using SQL | Fundamental SQL Statements, Database Restoration and Back-up, Filtering with Selection Commands, Ordering in Selection Commands, Alias Implementation, Application of Aggregate Commands, Utilizing Group By Commands, Conditional Statement Implementation, Understanding Joins, Execution of Subqueries, Usage of Views and Index, Implementing String Functions, Mathematical Functions Application, Date and Time Function Usage, Utilizing Pattern (String) Matching, Implementing User Access Control Functions |
| 3 | Extract, Transform and Load (ETL) | ETL Fundamentals, Data Source Identification, Data Extraction, Data Transformation, Data Mapping and Conversion, ETL Tools and Technologies, Data Loading, Batch and Real-time ETL, Error Handling and Logging, Performance Optimization, Automation, Monitoring and Maintenance |
| 4 | Tableau for Business Intelligence | Data Visualization, Introduction to Tableau, Tableau Workspace and Chart Types, Chart Creation and Data Preparation Techniques, Filters and Analytics in Tableau, Tableau Dashboards |
| 5 | Fundamentals of Python Programming | Programming Fundamentals, Introduction to Python, Python Data Types and Operators, Conditional Statements and Loops in Python, Python Functions, Object-Oriented Programming in Python, Threading in Python |
| 6 | Business Analytics With Python | Data Acquisition with APIs, Database Management with SQL and Python, Statistics Fundamentals, Probability Distributions, Advanced Statistics, Statistical Analysis with Python, Hypothesis Testing, Correlation and Regression Analysis, Time Series Analysis, ANOVA and Chi-Square Tests |
| 7 | Generative AI, Prompt Engineering & ChatGPT | Overview of Generative AI and its Landscape, Understanding Explainable AI, Exploring Conversational AI, Fundamentals of Prompt Engineering, Designing and Creating Effective Prompts, Extensive Language Models, ChatGPT: Applications and Functionality, Fine-tuning Strategies for ChatGPT, Ethical Considerations in Generative AI Models, Responsible Data Usage and Privacy Measures, AI Technologies Driving Innovation |
| 8 | Applications of Generative AI in Data Analytics | Real-world projects using skills in Excel, Python, SQL, Tableau, ETL processes, visualization techniques, ethical considerations, elective courses in generative AI, Power BI storytelling, R programming, or data ethics |
| 9 | Capstone Project | Real-world project using skills in Excel, Python, SQL, Tableau, ETL processes, visualization techniques, ethical considerations, elective courses in generative AI, Power BI storytelling, R programming, or data ethics |
| 10 | Mathematical Optimization for Business Problems By IBM | The Big Picture, Linear Programming, Network Models, Beyond Simple LP, Modelling Practice |
| 11 | Data Storytelling using Power BI | Efficient Data Retrieval and Preparation Techniques, Proficient Data Management, Interactive Report and Dashboard Creation, Efficiency-enhancing Power BI Tips and Tricks |
| 12 | Business Analytics With R Programming | Introduction to Business Analytics, Introduction to R Programming, Data Structures, Data Visualization, Statistics for Data Science I, Statistics for Data Science II, Regression Analysis, Classification, Clustering, Association |
| 13 | Data Ethics | Introduction to Data Ethics, Legal and Regulatory Frameworks, Data Privacy and Consent, Data Handling and Security, Transparency and Accountability, Bias and Fairness in Data Analysis, Ethical Decision-Making, Data Visualization and Communication, Ethics in Machine Learning and AI, Social and Ethical Impacts |
For even further depth in syllabus, check this out upGrad Doctor Of Business Administration Review
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