Conditional Formatting in Excel - Excel Training - Excel Tutorial for Beginners
Learn to enhance Excel data visualization with conditional formatting, including color scales, data bars, and icon sets. Master techniques for highlighting cells based on specific conditions.
Excel Formulas and Functions - Excel Tutorial for Beginners in 2021 - Great Learning
Learn essential Excel formulas and functions for data analysis and visualization. Master basic concepts, explore top functions, and gain practical skills to enhance your spreadsheet proficiency.
Jupyter Notebook Tutorial - How to Install Python Jupyter Notebook
Learn to install and use Jupyter Notebook for data science projects. Covers installation, key features, and a machine learning demo. Ideal for beginners and professionals looking to enhance their coding skills.
Build a Movie Recommendation System Using Python
Learn to build a movie recommendation system using Python, covering system types, implementation steps, and a hands-on demo. Gain practical skills in data manipulation and analysis for creating personalized movie suggestions.
Frequency Distribution
Learn to create and analyze frequency distributions, including types, tables, and Excel implementation. Gain practical skills for data representation and interpretation.
Boosting
Explore ensemble learning techniques like boosting to enhance machine learning performance. Learn about bias, variance, and popular algorithms for improved model accuracy and decision-making.
Python Beautiful Soup
Learn to extract web data efficiently using Python's Beautiful Soup library. Covers request module, library basics, and hands-on project for practical web scraping skills.
Multivariate Analysis
Explore multivariate analysis techniques for data-driven decision-making. Learn foundational concepts, practical implementation in Python, and applications across various domains.
Scikit-Learn
Learn to implement machine learning solutions using Scikit-learn, covering installation, algorithms, applications, advantages, and hands-on Python demos for data-driven decision-making.
Autocorrelation
Explore autocorrelation in data analytics: its concept, importance, testing methods, and applications. Includes a practical Python demo for hands-on learning and skill development.
Feature Engineering
Learn to optimize machine learning models through feature engineering techniques, from basic concepts to practical Python demonstrations, enhancing your data science skills.
SciPy in Python - Scientific Python Tutorial
Comprehensive tutorial on SciPy library for scientific computing in Python, covering installation, sub-packages, clusters, constants, FFTPack, interpolation, linear algebra, and image processing.
MySQL Playlist
Comprehensive MySQL tutorial covering installation, database operations, constraints, indexing, views, joins, and stored procedures, with interview preparation and query solving.
Statistics Playlist
Comprehensive journey through statistics for data science, from basics to advanced concepts, with hands-on Python implementation over 7 intensive sessions.
Machine Learning
Comprehensive 7-day exploration of key machine learning algorithms, from regression techniques to clustering methods, enhancing data science skills through live interactive sessions.
EDA and Feature Engineering Playlist
Hands-on sessions exploring data analysis and feature engineering using real-world datasets, covering Zomato, Black Friday sales, flight prices, and automated EDA techniques.
Time Series
Explore time series analysis through hands-on sessions covering EDA, stock analysis, and advanced forecasting models like ARIMA, SARIMAX, and Fbprophet.
Pre-Algebra Video Playlist
Comprehensive pre-algebra video series covering essential topics from basic arithmetic to geometry, with clear explanations and numerous examples for effective learning.
Using R
Learn advanced statistical techniques and data analysis using R, covering distributions, simulations, estimations, and various statistical tests through practical examples and hands-on coding.
Statistical Theory
Explore advanced statistical concepts, proofs, and applications using R, covering topics from probability distributions to matrix properties and confidence intervals.
Survival Analyses
Learn to generate censored exponential data, derive density and likelihood for censored data, and understand the Kaplan-Meier estimator as a maximum likelihood estimator in R.