Embark on a transformative journey into the dynamic realm of Knowledge 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:
– Acquire hands-on expertise in Python, a robust and versatile programming language broadly used for knowledge evaluation and manipulation.
– Study to leverage Python libraries akin to Pandas and NumPy for environment friendly knowledge dealing with and manipulation.
– Develop superior abilities in Excel, exploring its strong options for knowledge group, evaluation, and visualization.
– Harness the facility of Excel features and formulation to extract insights from advanced datasets.
– Purchase a stable basis in statistical ideas and strategies important for making knowledgeable selections based mostly on knowledge.
– Apply statistical strategies to interpret and draw significant conclusions from knowledge units.
– Discover your complete knowledge evaluation course of, from knowledge cleansing and preprocessing to exploratory knowledge evaluation (EDA) and have engineering.
– Learn to establish patterns, outliers, and developments inside datasets, enabling you to extract beneficial insights.
– Grasp the artwork of presenting knowledge visually by means of quite a lot of visualization instruments and strategies.
– 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 sort out real-world challenges and contribute meaningfully to data-driven decision-making in any skilled setting. Be a part of us on this journey to change into a proficient and sought-after tech skilled within the area 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 features, 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 Perform
Formatting Cells based mostly on Logical Features
Introduction to Textual content Features
Formatting cells based mostly on Textual content Features
Quiz on Logical Features, and Textual content Features
Knowledge Cleansing, and Characteristic engineering
Introduction to Date and Time Features
Fundamentals of Knowledge Cleansing in Excel
Fundamentals of Characteristic Engineering in Excel
Introduction to Energy Question in Excel
Quiz on Knowledge Cleansing and Characteristic Engineering
What If evaluation
Situation Supervisor
Purpose Search
Knowledge Tables
Solver Package deal
Quiz on What If evaluation
Charts and Dashboards
Knowledge Visualization Greatest Practices
Forms 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 Knowledge Sorts and Kind Casting
Scope of Variables
Introduction to Operators
Quiz on Fundamentals of Python
Introduction to Knowledge 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 Algorithms
Quiz on Knowledge 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 Record, Set and Dictionary Comprehensions
Introduction to Analytical and Combination Features
Quiz on Features in Python
Strings and Common Expressions
Introduction to Strings
Introduction to Essential String Features
Introduction to String Formatting and Person 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 Knowledge 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 Knowledge science
Forms of Knowledge
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 Chance
Introduction to Fundamental Chance
Introduction to Set Principle
Introduction to Conditional Chance
Introduction to Bayes Theorem
Introduction to Permutations and Combos
Introduction to Random Variables
Introduction to Chance Distribution Features
Quiz on Fundamental and Conditional Chance
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 Checks
Introduction to Z Checks
Introduction to Chi Squared Checks
Introduction to Anova Checks
Quiz on Speculation Testing
Knowledge Evaluation and Knowledge 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 Knowledge utilizing Pandas
Analyzing the Knowledge utilizing Pandas
Quiz on Introduction to Numpy and Pandas
Superior Features in Pandas
Indexing, Deciding on, and Filtering Knowledge
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
Forms of Charts and Visualizations
Components for good Knowledge Visualization
Introduction to Univariate Knowledge Visualizations
Introduction to Bivariate Knowledge Visualizations
Plotting two Categorical Variables
Introduction to Multivariate Knowledge Visualizations
Introduction to Heatmaps and Pairplots
Quiz on Forms of Charts and Visualizations
Superior Knowledge Visualizations
Colorscales, Side Grids, and Sub plots
Introduction to 3D Knowledge Visualization
Introduction to Interactive Knowledge Visualization
Introduction to Maps utilizing Plotly
Introduction to Funnel and Gantt Charts utilizing Plotly
Introduction to Animated Knowledge Visualizations utilizing Plotly
Quiz on Superior Knowledge Visualizations
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