Embark on a transformative journey into the dynamic realm of Information Analytics and Visualization, the place you’ll purchase important and sought-after tech abilities. This complete course is designed to empower you with proficiency in key instruments and methodologies, together with Python programming, Excel, statistical evaluation, knowledge evaluation, and knowledge visualization.
Key Studying Aims:
– Achieve hands-on expertise in Python, a robust and versatile programming language extensively used for knowledge evaluation and manipulation.
– Be taught to leverage Python libraries reminiscent of Pandas and NumPy for environment friendly knowledge dealing with and manipulation.
– Develop superior abilities in Excel, exploring its sturdy options for knowledge group, evaluation, and visualization.
– Harness the ability of Excel capabilities and formulation to extract insights from advanced datasets.
– Purchase a strong basis in statistical ideas and methods important for making knowledgeable choices primarily based on knowledge.
– Apply statistical strategies to interpret and draw significant conclusions from knowledge units.
– Discover the whole knowledge evaluation course of, from knowledge cleansing and preprocessing to exploratory knowledge evaluation (EDA) and have engineering.
– Discover ways to establish patterns, outliers, and developments inside datasets, enabling you to extract worthwhile insights.
– Grasp the artwork of presenting knowledge visually by way of a wide range of visualization instruments and methods.
– Use industry-standard instruments like Matplotlib and Seaborn to create compelling and informative knowledge visualizations.
Upon completion, you’ll possess a well-rounded talent set in knowledge analytics and visualization, equipping you to deal with real-world challenges and contribute meaningfully to data-driven decision-making in any skilled setting. Be a part of us on this journey to develop into a proficient and sought-after tech skilled within the subject of knowledge analytics and visualization.
Fundamentals of Excel
Excel Functions
Understanding the Excel Interface
Sorting and Filtering
Conditional Formatting
Quiz on Excel Fundamentals
Statistical and Mathematical Features in Excel
Introductions to Statistical Features
Introduction to Mathematical Features
Quiz on Statistical and Mathematical Features
Lookup capabilities, and Pivot Tables
Introduction to Lookup Features
Introduction to Index and Match
Introduction to Pivot Tables
Introduction to Pivot Charts
Quiz on Lookup Features, and Pivot Tables
Logical Features, and Textual content Features
Introduction to Logical Operate
Formatting Cells primarily based on Logical Features
Introduction to Textual content Features
Formatting cells primarily based on Textual content Features
Quiz on Logical Features, and Textual content Features
Information Cleansing, and Characteristic engineering
Introduction to Date and Time Features
Fundamentals of Information Cleansing in Excel
Fundamentals of Characteristic Engineering in Excel
Introduction to Energy Question in Excel
Quiz on Information Cleansing and Characteristic Engineering
What If evaluation
Situation Supervisor
Objective Search
Information Tables
Solver Bundle
Quiz on What If evaluation
Charts and Dashboards
Information Visualization Finest Practices
Varieties of Charts in Excel
Creating and Formatting Charts
Quiz on Charts and Dashboards
Fundamentals of Python
Actual world use circumstances of Python
Set up of Anaconda for Home windows and macOS
Introduction to Variables
Introduction to Information Sorts and Kind Casting
Scope of Variables
Introduction to Operators
Quiz on Fundamentals of Python
Introduction to Information Buildings
Introduction to Lists and Tuples
Introduction to Units and Dictionaries
Introduction to Stacks and Queues
Introduction to Area and Time Complexity
Introduction to Sorting Algorithms
Introduction to Looking out Algorithms
Quiz on Information Buildings
Introduction to Features in Python
Introduction to Parameters and Arguments
Introduction to Python Modules
Introduction to Filter, Map, and Zip Features
Introduction to Lambda Features
Introduction to Checklist, Set and Dictionary Comprehensions
Introduction to Analytical and Mixture Features
Quiz on Features in Python
Strings and Common Expressions
Introduction to Strings
Introduction to Necessary String Features
Introduction to String Formatting and Consumer Enter
Introduction to Meta Characters
Introduction to Constructed-in Features for Common Expressions
Particular Characters and Units for Common Expressions
Quiz on Strings and Common Expressions
Loops and Conditionals
Introduction to Conditional Statements
Introduction to For Loops
Introduction to Whereas Loops
Introduction to Break and Proceed
Utilizing Conditional Statements in Loops
Nested Loops and Conditional Statements
Quiz on Loops and Conditionals
OOPs and Date-Time
Introduction to OOPs Idea
Introduction to Inheritance
Introduction to Encapsulation
Introduction to Polymorphism
Introduction to Date and Time Class
Introduction to TimeDelta Class
Quiz on OOPs and Date-Time
Statistics and Speculation Testing for Information science
Introduction to Statistics and its significance
Clarify the position of statistics in knowledge evaluation
Introduction to Python for Statistical Evaluation
Quiz on Introduction to Statistics
Statistics and Speculation Testing for Information science
Varieties of Information
Measures of Central Tendency
Measures of Unfold
Measures of Dependence
Measures of Form and Place
Measures of Commonplace Scores
Quiz on Descriptive Statistics
Introduction to Fundamental and Conditional Likelihood
Introduction to Fundamental Likelihood
Introduction to Set Principle
Introduction to Conditional Likelihood
Introduction to Bayes Theorem
Introduction to Permutations and Combos
Introduction to Random Variables
Introduction to Likelihood Distribution Features
Quiz on Fundamental and Conditional Likelihood
Introduction to Inferential Statistics
Introduction to Regular Distribution
Introduction to Skewness and Kurtosis
Introduction to Statistical Transformations
Introduction to Pattern and Inhabitants Imply
Introduction to Central Restrict Theorem
Introduction to Bias and Variance
Introduction to Most Probability Estimation
Introduction to Confidence Intervals
Introduction to Correlations
Introduction to Sampling Strategies
Quiz on Inferential Statistics
Introduction to Speculation Testing
Fundamentals of Speculation Testing
Introduction to T Assessments
Introduction to Z Assessments
Introduction to Chi Squared Assessments
Introduction to Anova Assessments
Quiz on Speculation Testing
Information Evaluation and Information Viz : Introduction to Numpy and Pandas
Introduction to Numpy Arrays
Introduction to Numpy Operations
Introduction to Pandas
Introduction to Sequence and DataFrames
Studying CSV and JSON Information utilizing Pandas
Analyzing the Information utilizing Pandas
Quiz on Introduction to Numpy and Pandas
Superior Features in Pandas
Indexing, Deciding on, and Filtering Information
Merging and Concatenation utilizing Pandas
Correlation and Plotting utilizing Pandas
Introduction to Lambda, Map and Apply Features
Introduction to Grouping Operations utilizing Pandas
Introduction to Cross Tabulation utilizing Pandas
Introduction to Filtering Operations utilizing Pandas
Interactive Grouping and Filtering Operations
Quiz on Superior Features in Pandas
Varieties of Charts and Visualizations
Elements for good Information Visualization
Introduction to Univariate Information Visualizations
Introduction to Bivariate Information Visualizations
Plotting two Categorical Variables
Introduction to Multivariate Information Visualizations
Introduction to Heatmaps and Pairplots
Quiz on Varieties of Charts and Visualizations
Superior Information Visualizations
Colorscales, Aspect Grids, and Sub plots
Introduction to 3D Information Visualization
Introduction to Interactive Information Visualization
Introduction to Maps utilizing Plotly
Introduction to Funnel and Gantt Charts utilizing Plotly
Introduction to Animated Information Visualizations utilizing Plotly
Quiz on Superior Information Visualizations
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