Data Science Foundations Academy

Mission 1 - Data Cleaning

• Description: In this mission, you will learn the fundamental skills of loading and cleaning real-world datasets, focusing on an online retail dataset. Data cleaning is a crucial step in data preprocessing for machine learning and analysis.
• Learning Topics: Data loading, Pandas usage, handling data types, missing value detection and handling, duplicate entry identification, data inconsistency resolution.
• Learning Goals: By the end of this mission, you will be proficient in cleaning and preparing datasets for further analysis, an essential skill for data scientists.

Mission 2 - Business Data Analysis

• Description: This mission is about answering business-related questions using the online retail dataset, leveraging Pandas for data manipulation. Analyzing data for business insights is a key application of data science.
• Learning Topics: Filtering and subsetting data, joining and merging datasets, performing group-by operations, sorting data, setting and resetting indexes.
• Learning Goals: After this mission, you will have the skills to extract meaningful business insights and make data-driven decisions.

Mission 3 - Descriptive Statistics and Visualization

• Description: In this mission, you will explore the world of descriptive statistics, focusing on the use of a house prices dataset. You will also learn the importance of data visualization to spot patterns.
• Learning Topics: Calculating mean, median, mode, quantiles, data visualization, outlier detection, correlation analysis.
• Learning Goals: Your ability to summarize data, visualize it effectively, and detect outliers will be enhanced, enabling you to make data-informed decisions.

Mission 4 - Probability and Statistics Concepts

• Description: This mission introduces probability and statistics concepts, including probability basics, probability distributions, and their real-life applications.
• Learning Topics: Probability basics, probability distributions, probability mass/density functions, cumulative distribution functions, expected value, variance, famous probability distributions.
• Learning Goals: You'll have a solid understanding of the fundamental concepts in probability and statistics, which are essential for data modeling and analysis.

Mission 5 - Central Limit Theorem and Hypothesis Testing

• Description: This mission delves into the Central Limit Theorem, confidence intervals, hypothesis testing, and A/B testing, key tools for making inferences and testing hypotheses.
• Learning Topics: Central Limit Theorem, confidence intervals, hypothesis testing, A/B testing.
• Learning Goals: You'll be equipped to make inferences about populations, test hypotheses, and conduct A/B tests with statistical confidence.

Mission 6 - Association Analysis and Bayesian Inference

• Description: In this mission, you'll learn to measure the strength of associations between variables and explore Bayesian Inference, broadening your statistical reasoning skills.
• Learning Topics: Contingency tables, marginal and conditional probabilities, Bayes' Theorem, Chi-Square Test, Cramer's V measure.
• Learning Goals: You'll gain expertise in association analysis and Bayesian Inference, expanding your analytical toolkit for data-driven decision-making.

Mission 7 - Independent Data Analysis

• Description: This mission challenges you to independently analyze a credit card score dataset, avoiding common data science pitfalls. You'll learn to formulate business questions and conduct exploratory data analysis (EDA).
• Learning Topics: Avoiding data science pitfalls, formulating business questions, conducting EDA.
• Learning Goals: By the end of this mission, you'll be capable of applying all your skills to analyze new data independently and provide valuable insights, a crucial skill for data scientists.