Data Analytics Online Beginner level by Antrix Academy of Data Science

Data Analytics With Python

30 +hrs.
Live Mentoring
40 +hrs.
Coding Assignments
4+
Real-Life Projects
3+
Industry cases

Modules Included
Introduction to Python Programming
Why do we need Python?

Program structure in Python

Interactive Shell

Executable or script files.

User Interface or IDE

Data Type and Operations
Numbers

Strings

List

Tuple

Dictionary

Other Core Types

Statements and Syntax in Python
Assignments, Expressions and prints

If tests and Syntax Rules

While and For Loops

Iterations and Comprehensions

File Operations
Opening a file

Using Files

Other File tools

Function in Python
Function definition and call

Function Scope

Arguments

Function Objects

Anonymous Functions

Python:Data Manipulation - Cleansing
Important Python Packages for data manipulation (Pandas, Numpy etc)

Cleansing Data with Python

Data Manipulation steps(Sorting, filtering, duplicates, merging, appending, subsetting, derived variables, sampling, Data type conversions, renaming, formatting etc)

Data manipulation tools(Operators, Functions, Packages, control structures, Loops, arrays etc)

Python Built-in Functions (Text, numeric, date, utility functions)

Python User Defined Functions

Stripping out extraneous information

Normalizing data

Formatting data

Python:Accessing/Importing and Exporting Data
Re-visiting Python Packages (Pandas, Numpy etc)

Importing Data from various sources (Csv, txt, excel, access etc)

Database Input (Connecting to database)

Data manipulation tools(Operators, Functions, Packages, control structures, Loops, arrays etc)

Viewing Data objects - subsetting, methods

Exporting Data to various formats

Python:Data Analysis - Visualization
Introduction exploratory data analysis

Creating Graphs-Bar/pie/line chart/histogram/boxplot/scatter/density etc) using Matplotlib, Pandas, etc.

Python:Statistics
Statistics Concepts

Descriptive statistics, Frequency Tables and summarization

Univariate Analysis (Distribution of data & Graphical Analysis)

Central Tendencies – Mean, Mode, Median, Probability, Probability Distribution

Type of RV – Nominal, Ordinal, Interval, Ratio; Variance, Standard Deviation

Inferential Statistics

Hypothesis Testing

> z test & t test
Python:Machine Learning Concept