Data Analytics Foundations
Skills Gained
- Proficiency in R programming language, specifically in using Jupyter Notebooks
- Familiarity with the data analytics process, including data collection, exploratory data analysis, and data visualization
- Ability to conduct EDA using tidyverse, ggplot2 and other libraries in R
Learning Outcomes
This module aims to introduce you to the fundamentals of data analysis using R programming language and popular packages like tidyr and ggplot2. By the end of this module, you should have a basic understanding of how to manipulate, analyze, and visualize data using R.
Data Wrangling with R
Skills Gained
- Proficiency in assessing data quality and identifying data issues
- Knowledge of various data cleaning techniques and the ability to apply them using R
- Ability to transform data into a format suitable for analytics using R
Learning Outcomes
In this module, you will gain the necessary skills to effectively gather, assess, clean, and transform data using R. These skills will help you handle real-world data challenges and prepare data for analysis.
Statistical Based Analysis
Skills Gained
- Understanding of probability, distributions, and the central limit theorem
- Ability to interpret confidence intervals
- Familiarity with hypothesis testing and A/B testing
- Knowledge of linear and logistic regression and their applications to data analysis
Learning Outcomes
The goal of this module is to provide a comprehensive understanding of statistical analysis concepts and techniques, including probability, distributions, central limit theorem, and much more.
Data Analytics with Excel
Skills Gained
- Ability to explore data using Excel’s built-in features like filtering, sorting, and conditional formatting
- Understanding of different data types and how
- Ability to prepare data for analytics, including reshaping data and using formulas and functions
Learning Outcomes
This module aims to teach you the fundamentals of data analysis using Microsoft Excel. By the end of this module, you should be able to use Excel to explore, clean, prepare, and analyze data.
Machine Learning Basics
Skills Gained
- Acquire foundational knowledge of Artificial Intelligence and its applications
- Develop skills in major machine learning algorithms
- Gain expertise in assessing the performance of machine learning models
Learning Outcomes
In this module you will develop skills in major machine learning algorithms, allowing you to proficiently apply them to various tasks. You will gain expertise in assessing the performance of machine learning models, employing relevant metrics to evaluate accuracy, precision, recall, and other key indicators.
Exploring Databases
Skills Gained
- Knowledge of the different types of databases
- Ability to distinguish between relational and non-relational databases
- Basic understanding of SQL and its usage in database querying and manipulation
Learning Outcomes
In this module, you will learn about databases, their types, and their importance in the world of data. You will gain an understanding of relational and non-relational databases, and learn the basics of SQL.
Storytelling with Data
Skills Gained
- Choosing the appropriate type of graph for your visualization
- Recognizing the clutter clouding your information
- Utilizing business intelligence tools to build an effective story
Learning Outcomes
The goal of this module is to teach you how to effectively communicate insights and patterns in your data through various types of visualizations such as univariate, bivariate, and multivariate plots. You will also discover tools and techniques to create an engaging and informative story. In order to achieve this, you will explore some business intelligence tools such as Tableau and Power BI.
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