Data Analytics FULL Course for Beginners to Pro in 29 HOURS – 2024 Edition

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Data Analytics FULL Course for Beginners to Pro in 29 HOURS – 2024 Edition

πŸ”΄ To learn Data Analytics Course online with regular LIVE CLASSES, enroll now: https://www.wscubetech.com/landing-pages/online-data-analytics-course.html?utm_source=YouTube&utm_medium=JAN2024_04&utm_campaign=RV

GitHub Link: https://github.com/Ayushi0214/Datasets

00:00:00 – 02:15:26: Python Basics
– Introduction to Python for Data Analytics
– Python Installation in Windows
– Python IDE (Pycharm)
– First Program in Python
– Comments, Variables, Datatypes, User-Inputs
– TypeCasting, Subtypes, Problem-Solving
– Operators and Operands
– Conditional Statements

02:40:22 – 06:36:18: Python – Loops and Lists
– Introduction to Loops
– For Loop, While Loop, Nested Loops
– For Loop with Conditional Statements
– Break and Continue Statement
– Loops Problem Solving
– Introduction to Lists
– Lists Slicing, Iteration, Functions
– List Comprehension, Problem Solving

06:47:43 – 07:36:16: Tuples, Dictionaries, and Sets in Python
– Introduction to Tuples
– Tuples Slicing, Iteration, Functions, Problem Solving
– Introduction to Dictionaries
– Iteration, Functions, Nested Dictionaries, Problem Solving
– Introduction to Sets
– Set Methods, Problem Solving

08:16:10 – 09:14:20: Python Functions and Modules
– Introduction to Functions
– Parameters, Arguments, Return Statement, Recursion
– Lambda Function, Local and Global Variables
– Functions Problem Solving
– Introduction to Modules, In-built Modules
– Creation of Modules, Project Random Module

09:15:59 – 15:57:26: Numpy and Data Manipulation
– Introduction to Numpy
– Installation of Jupyter Notebook
– Creation, Indexing, and Slicing of Numpy Arrays
– Mathematical Operations, Combining and Splitting Arrays
– Search, Sort, Filter Arrays, Aggregating Functions
– Statistical Functions in Arrays

12:01:26 – 13:45:36: Pandas for Data examination
– Introduction to Pandas
– Creation of Data Frames, Exploring Data
– Dealing with Duplicate values, Missing Data
– Column Transformation in Pandas, GroupBy
– Merge, Concatenate, Join in Pandas
– Pivoting and Melting Dataframes

13:43:51 – 15:57:26: Matplotlib for Data Visualization
– Introduction to Matplotlib
– Bar, Line, Scatter, Pie, Box, Histogram, Violin, Stem plots
– Stack Plot, Step Chart, Legends, Subplot
– Save a Chart Using Matplotlib
– Data Visualization in Seaborn
– Seaborn Project

18:38:09 – 21:02:52: MySQL for Data Analytics
– Introduction to MySQL
– Installation, Importing Data
– Select Query, Where Clause
– AND, OR, NOT Operators, Like Operator
– Order By, Limit, Between
– IN, NOT IN operator, String Functions
– Data Aggregation, Numeric Functions
– Date Functions, Case Operator
– Group By, Having Clause
– Joins, Set Operators, Subqueries, Views
– Stored Procedure, Window Functions

21:14:31 – 24:45:52: Excel for Data Analytics
– Introduction to MS Excel
– Basic Functions, Data Validation
– Data Connectors, Conditional Formatting
– Basics of Formatting, Sorting, Filtering Data
– Dealing with Null Values, Duplicate Values
– Trimming Whitespaces, Text Functions
– IF, AND, OR Functions, Date & Time Functions
– COUNTIF, SUMIF Functions, Xlookup
– Power Query, Cleaning and Transformation
– Creating a Dashboard in Excel, myExcel Project

25:38:35 – 29:09:56: Power BI Essentials
– Introduction to Power Bi
– Installation of Power Bi Desktop
– Data Connectors, Basic Transformations
– Format Tool, Pivoting, Unpivoting of data
– Adding Conditional Columns, Merge queries
– Data model, Relationship Management
– Introduction to DAX, Calculated Columns, Measures
– DAX Functions, Visualizations, Filters
– Creating Reports, Custom Visuals
– Designing for telephone vs Desktop Report Viewers
– Publishing Reports to Power BI Services

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