Data Science Course has helped more than 1,000 professionals to switch and get 50% to 300% Salary hikes

** What's Inside?**

01
INTRODUCTION TO DATA SCIENCE

1. Data
2. What is Data Science?
3. Understand Data Scientist, Data Analyst & Data Engineer
4. Market TREND
5. JOB Opportunities
6. How to become Data Scientist?
7. What cover Data Science
8. Roadmap

02
PYTHON

i. Introduction of Python
ii. Installing Python IDES – Python IDLE and Anaconda
iii. Writing Your First Python Program
iv. Data-types in Python
v. Variables in Python – Declaration and Use
vi. Typecasting in Python
vii. Operators in Python – Assignment, Logical, Arithmetic etc.
viii. Taking User Input (Console)
ix. Conditional Statements – If else and Nested If else and elif
x. Python Collections (Arrays) – List, Tuple, Sets and Dictionary
xi. Loops in Python – For Loop, While Loop & Nested Loops
xii. String Manipulation – Basic Operations, Slicing & Functions and Methods
xiii. User Defined Functions – Defining, Calling, Types of Functions, Arguments
xiv. Lambda Function
xv. Importing Modules – Math Module
xvi. Basics of Object Oriented Programming
xvii. Creating Class and Object
xviii. Constructors in Python – Parameterized and Non-parameterized
xix. Inheritance in Python
xx. In built class methods and attributes
xxi. Multi-Level and Multiple Inheritance
xxii. Method Overriding and Data Abstraction

03
SQL, Databases

a. Introduction to Databases
b. Need of Databases
c. Database Softwares
d. Market Trends in Databases
e. MS SQL Server
f. SQL
g. Why SQL?
h. DDL/DML/DCL
i. DataTypes
j. Keys
k. Constraints
l. Understanding Select Statement
m. Usage of Top, Distinct, Null etc...keywords
n. Using String and Arithmetic Expressions
o. Using functions in Queries
p. Count, Sum, Min, Max, Avg
q. Group By and Having Clause
r. Joins and Set Operations
s. Views
t. Cursor
u. Trigger
v. Index
w. Stored Procedures
x. User Defined Functions

04
Statistics

a. Introduction to Statistics
b. Data, Data Category, Data Types
c. Sample and Population
d. Descriptive & Inferential Statistics
e. Central Tendency
f. Mean, Median, Mode, STD, Variance
g. Covariance & Correlation & Coefficient
h. Distribution
i. Normal Distribution
j. Uniform Distribution
k. Estimation
l. Confidence Interval
m. Hypothesis Testing

05
CLOUD

a. Cloud System
b. AWS, AZURE, GCP
c. What is Azure?
d. Azure Data Factory
e. Azure Active Directory
f. Azure Virtual Network

06
INTRO TO POWER BI

a. Introduction to Power BI
b. Installtion
c. Data Sources
d. Loading
e. View
f. Query Editor
g. Transform, Clean, Shape and Model Data
h. DAX
i. DAX Syntax
j. Charts
k. Power BI Service