[Infographic] Data Science Learning Checklist

A career in data science is highly sought-after and lucrative. It encompasses a range of tasks such as studying and organizing data, applying machine learning techniques, and being aware of business objectives. To excel in this field, you should have a combination of abilities, like scrutinizing data, grasping business concepts, communication proficiencies, and more. To aid in your progress, use this list as a reference point in your learning journey.

To download this infographic, press on the image above

Exploratory Data Analysis

Descriptive Statistics

• Calculate metrics on measures of location like mean and median, measures of variation like range and standard deviation, and other characteristics of features
• Calculate metrics like correlation to understand the relationships between feature

Learn on DataCamp

Apply Your Skills

• A Visual History of Nobel Prize Winners
• Optimizing Online Sports Retail Revenue
• Explore a DataFrame
• Analyzing Carbon Footprints in SQL
• Exploring World Cup Data in Python

Data Visualization

• Create plots like bar plots, histograms and box plots to visualize single features.
• Create plots like scatter plots, line plots and heat maps to visualize relationships between features.

Learn on DataCamp

Apply Your Skills

• Visualizing COVID-19 in R
• Modeling the Volatility of US Bond Yields in R
• Exploring the Bitcoin Cryptocurrency Market in Python
• Real-time Insights from Social Media Data in Python
• Visualize Correlation with a Diagonal Correlation Plot in Python
• Data Visualization in Python for Absolute Beginners
• Visualizing Video Game Sales Data with ggplot2 in R

Data Management

Importing & Reading Data

• Import data from common file formats like CSV and spreadsheets.
• Import data by querying SQL databases.
• Import data via web APIs.

Learn on DataCamp

Apply Your Skills

• Importing and Cleaning Data
• The Android App Market on Google Play
• Visualize Historical Stock Data with a Candlestick Chart
• Analyzing Streaming Service Content in SQL
• Analyzing Students' Mental Health in SQL

Data Wrangling

• Perform common data manipulations such as sorting, subsetting, adding new features, and aggregating.
• Join two datasets together via inner, left and other joins.
• Pivot a rectangular dataset to convert rows to columns or columns to rows.

Learn on DataCamp

Apply Your Skills

• What and Where are the World's Oldest Businesses?
• Streamlining Employee Data
• Merge DataFrames
• Analyzing NASA Planetary Exploration Budgets in SQL

Data Cleaning

• Identify and fix issues with data constraints such as wrong data types, numbers out of range, or duplicate values.
• Identify and fix issues with text and categorical data, such as invalid categories or incorrect formatting.
• Identify and fix issues with data uniformity, such as incorrect units, incorrect date formats, and inconsistency between features.
• Identify and fix issues with missing data values.

Learn on DataCamp

Apply Your Skills

• Exploring the Bitcoin Cryptocurrency Market in Python
• Real-time Insights from Social Media Data in Python

Business Acumen

Business Goals

• Make recommendations for analytic approaches based on business goals
• Judge performance of analytic results against KPIs or other relevant business criteria

Learn on DataCamp

Apply Your Skills

• Comparing Search Interest with Google Trends
• Optimizing Online Sports Retail Revenue
• Predict CTR and Evaluate ROI
• Calculate Customer Churn Metrics

Organizational Knowledge

• Understand the impact of data science projects on your business.
• Understand which teams or employees need to be involved in a data project, and in what capacity.

Learn on DataCamp

Apply Your Skills

• Which Debts Are Worth the Bank's Effort?
• Feature Engineering for Fraud Detection
• User Retention by Cohort
• Analyzing a Marketing Funnel in Spreadsheets
• Visualizing Cost Savings in Tableau

Programming for Data Science

Computational Thinking

• Use common programming constructs like flow control and iteration.
• Understand functions and functional programming to write repeatable code for analysis.

Learn on DataCamp

Apply Your Skills

• Functions for Food Price Forecasts
• Writing Functions for Product Analysis
• Group and Aggregate data with custom functions

Production Coding

• Make use of version control like git for managing code
• Use error handling, assertions, and unit tests to ensure code quality
• Write documentation to make your code understandable by others
• Develop packages to make your code reusable

Learn on DataCamp

Apply Your Skills

• Functions for Food Price Forecasts
• Writing Functions for Product Analysis

Model Development

Model Design

• Choose an appropriate model type (regression, classification, clustering, etc.) based on your dataset and the analysis goals

Learn on DataCamp

Apply Your Skills

• Predicting Credit Card Approvals
• Predict Taxi Fares with Random Forest
• Classify Song Genres from Audio Data
• Find Movie Similarity from Plot Summaries
• Clustering Heart Disease Patient Data
• ASL Recognition with Deep Learning
• Disney Movies and Box Office Success

Feature Engineering

• Extract problem-relevant information from existing features, like getting the day of week from a datetime variable, or getting an "is working age" indicator from a date of birth.
• Combine multiple features into new features, for example summing regional sales into total sales, or calculating profit as revenue minus costs.
• Use external datasets to define new features, for example using a geographic API to get the city from a longitude and latitude, or using a computer vision API to determine if an image contains people.
• Use imputation to estimate missing values.

Learn on DataCamp

Apply Your Skills

• Customer Analytics: Preparing Data for Modeling
• Predict Taxi Fares with Random Forest
• Classify Song Genres from Audio Data
• Find Movie Similarity from Plot Summaries
• Encoding Categorical Variables
• Sentiment Analysis and Prediction in Python

Model Fitting

• Can generate training and testing splits from a dataset, including using cross-validation.
• Uses hyperparameter tuning to optimize model performance.

Learn on DataCamp

Apply Your Skills

• What Makes a Pokémon Legendary?
• Predict Taxi Fares with Random Forests
• Machine Learning with Python
• Machine Learning with R
• Predicting Hotel Booking Cancellations in Python
• Analyzing a Time Series of the Thames River in Python

Model Validation

• Can evaluate supervised learning model performance using metrics like accuracy, precision and recall.
• Can evaluate unsupervised learning model performance using metrics like homogeneity, completeness, and silhouette coefficient.

Learn on DataCamp

Apply Your Skills

• Clustering Bustabit Gambling Behavior
• Degrees That Pay You Back
• Evaluate your ML Model using the F-score
• How to Explain Black-Box Machine Learning Models

Statistical Experimentation

Sampling Methods

• Understand statistical distributions like the normal, uniform and Poisson distributions
• Choose appropriate sampling methods to answer your questions while avoiding bias.

Learn on DataCamp

Apply Your Skills

• Health Survey Data Analysis of BMI

Hypothesis Testing

• Understand null and alternative hypotheses
• Know when and how to use hypothesis tests like the t-test, Chi-squared test, and Mann-Whitney U test
• Interpret test statistics and p-values

Learn on DataCamp

Apply Your Skills

• Dr. Semmelweis and the Discovery of Handwashing
• Mobile Games A/B Testing with Cookie Cats

Data Communication

Data Storytelling

• Create a narrative that describes your motivation, methods, results, and conclusions
• Ensure your narrative is consistent with the findings of the data
• Edit your stories to remove extraneous details

Learn on DataCamp

Apply Your Skills

• Tips for Reporting in Workspace
• Data Visualization in Python for Absolute Beginners

Understand your Audience

• Understand your audience's prior knowledge and interests
• Tailor your message to resonate with the audience, even if they are non-technical

Learn on DataCamp

Apply Your Skills

• Exploring World Cup Data in Python