77 Languages
English
Français
Español
Deutsch
Italiano
中文
हिंदी
العربية
Русский
Português
日本語
한국어
Türkçe
Polski
Nederlands
Magyar
Čeština
Svenska
Norsk
Dansk
Kiswahili
ไทย
বাংলা
فارسی
Tiếng Việt
Filipino
Afrikaans
Shqip
Azərbaycanca
Беларуская
Bosanski
Български
Hrvatski
Eesti
Suomi
ქართული
Kreyòl Ayisyen
Hawaiian
Bahasa Indonesia
Gaeilge
Қазақша
Lietuvių
Luganda
Lëtzebuergesch
Македонски
Melayu
Malti
Монгол
မြန်မာ
Norsk
فارسی
ਪੰਜਾਬੀ
Română
Samoan
संस्कृतम्
Српски
Sesotho
ChiShona
سنڌي
Slovenčina
Slovenščina
Soomaali
Basa Sunda
Kiswahili
Svenska
Тоҷикӣ
Татарча
ትግርኛ
Xitsonga
اردو
ئۇيغۇرچە
Oʻzbek
Cymraeg
Xhosa
ייִדיש
Yorùbá
Zulu
Apprentice Mode
10 Modules / ~100 pages
Wizard Mode
~25 Modules / ~400 pages
🎓
CREATE AN EVENT
Data Analysis
( 24 Modules )
Module #1
Introduction to Data Analysis
Overview of data analysis, importance, and applications
Module #2
Data Types and Sources
Types of data, data sources, and data collection methods
Module #3
Data Preparation and Cleaning
Importance of data cleaning, dealing with missing values, and data transformation
Module #4
Data Visualization Basics
Introduction to data visualization, types of plots, and best practices
Module #5
Descriptive Statistics
Measures of central tendency, variability, and data distribution
Module #6
Data Summarization and Aggregation
Data aggregation, grouping, and summarization techniques
Module #7
Data Visualization for Univariate Analysis
Visualizing single variables using histograms, box plots, and more
Module #8
Data Visualization for Bivariate Analysis
Visualizing relationships between two variables using scatter plots and more
Module #9
Introduction to Inferential Statistics
Basics of inferential statistics, sampling distributions, and confidence intervals
Module #10
Hypothesis Testing
Formulating hypotheses, types of tests, and test assumptions
Module #11
Confidence Intervals and Estimation
Constructing confidence intervals and estimating population parameters
Module #12
ANOVA and Regression Analysis
Analysis of variance, simple and multiple regression, and model building
Module #13
Time Series Analysis
Introduction to time series analysis, components, and model building
Module #14
Forecasting Methods
Exponential smoothing, ARIMA, and other forecasting techniques
Module #15
Data Mining and Machine Learning
Overview of data mining, machine learning, and supervised learning
Module #16
Supervised Learning Algorithms
Decision trees, random forests, and other supervised learning algorithms
Module #17
Unsupervised Learning Algorithms
Clustering, k-means, and hierarchical clustering
Module #18
Text Analytics and Natural Language Processing
Introduction to text analytics, NLP, and sentiment analysis
Module #19
Data Analysis with Python
Using Python for data analysis, pandas, NumPy, and Matplotlib
Module #20
Data Analysis with R
Using R for data analysis, data manipulation, and visualization
Module #21
Data Analysis with Excel
Using Excel for data analysis, pivot tables, and charting
Module #22
Big Data Analytics
Introduction to big data, Hadoop, and Spark
Module #23
Data Storytelling and Communication
Effectively communicating insights and results to stakeholders
Module #24
Course Wrap-Up & Conclusion
Planning next steps in Data Analysis career
Ready to Learn, Share, and Compete?
Create Your Event Now
Language Learning Assistant
with Voice Support
Hello! Ready to begin? Let's test your microphone.
▶
Start Listening
Copyright 2025 @ WIZAPE.com
All Rights Reserved
CONTACT-US
PRIVACY POLICY