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Learn to generate realistic mock sales data using Python libraries like NumPy, Pandas, and Datetime. Create datasets with varied product purchases, timestamps, and addresses for data science practice.
Learn to create and customize line graphs and bar charts using Matplotlib in Python, covering essential visualization techniques like styling, scaling, and annotating plots.
Comprehensive tutorial on Python Pandas for data science, covering data loading, manipulation, analysis, and advanced techniques for handling large datasets.
Comprehensive tutorial on pseudo-bulk analysis for single-cell RNA-Seq data, covering the what, why, and how. Includes data manipulation, aggregation, and differential expression analysis using R, Seurat, and DESeq2.
Comprehensive tutorial on analyzing single-cell RNA-Seq data using Seurat in R, covering data processing, quality control, normalization, dimensionality reduction, and clustering for genomics research.
Learn to visualize gene expression data using R and ggplot2. Create barplots, density plots, boxplots, scatterplots, and heatmaps from RNA-Seq data. Hands-on tutorial for beginners in bioinformatics.
Learn to manipulate gene expression data from NCBI GEO using R and dplyr. Covers data reading, metadata retrieval, and essential dplyr functions for effective bioinformatics analysis.
Learn to build a data science portfolio website using Hugo and host it on Hostinger. Covers site creation, customization, and cloud deployment for showcasing your skills and achievements effectively.
Explore how Notion enhances productivity for a professor and content creator in data science. Learn practical use cases, customization tips, and benefits for teaching, content creation, and portfolio building.
Learn to adapt machine learning code in R for new datasets. Explore data understanding, visualization, and model building techniques using the DHFR dataset as an example.
Explore advanced SQL Server Reporting Services techniques for data analysis, including filters, parameters, visualizations, and map creation to enhance your reporting capabilities and meet evolving business needs.
Practical guide to image classification using CIFAR10 dataset. Learn to load data, create DataLoaders, transform images, and visualize the dataset in PyTorch for computer vision tasks.
Learn essential SQL skills for data science, including SELECT, JOIN, aggregations, CTEs, and window functions. Apply these techniques to time series forecasting and fraud prediction.
Explore data science techniques for fraud detection, including feature engineering, SQL querying, model creation, evaluation, and interpretation, with hands-on coding examples.
Comprehensive guide to A/B testing for data scientists, covering experiment design, dataset creation, hypothesis testing, Bayesian methods, and result interpretation using practical examples and code.
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