Skill Degree in Data Analytics

More Than 10k+ Students
80% Students Placed
5.9 LPA Average CTC
10 LPA Highest CTC
100+ Expert Mentors
8 Years in Industry
50+ Hiring Parteners
Hybrid Classes
100% Job Placement
4.7 Rating on Google

Course Description

Discover the world of data analytics at Skill Circle, where our comprehensive course covers fundamental principles such as data collection and exploration. Gain proficiency in data manipulation and analysis using industry-standard tools like Python and SQL. Additionally, learn to transform raw data into compelling visual narratives with Power Bl, creating interactive dashboards that convey insights effectively. Dive into advanced analytics using Tableau, where you’ll uncover patterns and trends through sophisticated visualizations.

When you choose Skill Circle, you benefit from experienced instructors offering practical insights and real-world applications. Apply your skills to hands-on projects, building a robust portfolio that showcases your proficiency. Our flexible learning options are designed to accommodate both full-time professionals and students.

Program Key Features

4 Months of Live Advance Learning.
Advanced Stimulation Training with Student
14+ Modules with Globally Recognised Certification
10+ Capstone Projects with Dedicated Mentors from Industry
Interview Preparation Sessions by HR working at naukri.com
100% Placement Assistance at our inHouse #Jobcircle Portal

What You’ll Learn From This Course?

The functioning of the Digital Landscape
Auditing the brands digitally
Digital strategy and planning along with latest tools, trends and practices
Working on live projects under expert guidance
Advanced courses like, Domain Flipping, Freelancing, Podcast Marketing, and Personality Development.

Why you should learn Data Analytics?

⦁ Smart Decision-Making: Data Analytics empowers you to make informed decisions by revealing patterns and insights within large sets of information.

⦁ Career Advancement: Acquiring Data Analytics skills enhances your employability, as industries increasingly

⦁ Problem-Solving: Become a problem solver by using data-driven approaches to address challenges and find effective solutions.

⦁ Technological Impact: Gain the ability to leverage technology for positive change, applying Data Analytics in various fields for real-world impact.

⦁ Creative Expression: Data Analytics is not just about numbers; it’s a canvas for creativity. Visualize data to tell compelling stories and make information accessible.

⦁ Global Relevance: In a world driven by data, learning Data Analytics provides you with a universal language to navigate and understand the dynamics of various industries worldwide.

Program Curriculum

Introduction To Data Analytics

Introduction to Data Analytics
Introduction to Data Science
Applications and impact in various industries
Benifits of Data Analytics for Businesses.

Data Analytics With Excel

Basics for Excel
Data Formatting
Data Calculations
Data Automation
Sorting and Flteration

Excel Data Functions

IF Functions
COUNTIF, SUMIF
VLOOKUP

Table And Dashboarding

Pivot Tables
Analysis using
Pivot Table
Charts
Dashboarding

Statistics For Data Analytics

Variables in
Qualitative and Quantitative
Population and Sampling
Sampling Techniques

Descriptive Statistics

Measure Of Central Tendency
Measure of Dispersion
Normal Distribution
Skewness and Kurtosis

Inferential Statistic

Hypothesis Testing
Methods
T-Test I Z-Test I Chi-Square Test
ANOVA

Probabilities

Probability basics
Common probability distributions
Sampling and the Central Limit Theorem

Python For Data Analytics

Introduction to Python
Syntax Understanding in Python
Variables in python
Operators in python
Built-in keywords and Methods in Python
Data Types in Python
Data Structures in Python

Intermediate

Flow Control Statements
If Else Statements
Loops
Defining a Function
Lambda, Map, Reduce and Filter functions

Advance

Classes and Objects (OOPs)
Constructors in Python.
Destructors in Python.
Inheritance in Python
File Handling and Exceptions

Exploratory Data Analytics (eda)

Introduction to Exploratory Data Analytics
Libraries and Modules used for EDA
Import and Export Data.
Getting Data from Web Sources

Numpy

Introduction to NumPy and its importance in EDA
Introduction to Array's
Numpy arrays: Creating, indexing, and slicing

Data Manipulation With Numpy

Array reshaping and dimensions
Concatenating and splitting arrays
Array filtering and boolean indexing
Array sorting and searching
Working with missing data

Numerical Computations

Basic statistical functions in NumPy
Linear algebra operations with NumPy
Random number generation with NumPy

Pandas

Introduction to Pandas and its role in EDA
Series and DataFrame data structures
Data indexing, selection, and filtering
Basic operations on Series and DataFrames

Data Cleaning And Preprocessing

Handling missing data in Pandas
Data deduplication and data type conversion
Merging and joining DataFrames
Working with time series data

Data Analysis With Pandas

Descriptive statistics and data summarization
Grouping and aggregation in Pandas
Pivot tables with pandas
Working with text data in Pandas

Data Visualization

Introduction to data visualization and its importance in EDA
Basic Visualizations concepts (figure, axes, plots)
Understanding Line plots, scatter plots, and bar plots etc.

Matplotlib

Basic Plotting with Matplotlib
Introduction to Matplotlib
Create Basic Plots
Customization of Plots
Plot's Formatting
Adding Annotations
Creating Subplots and Multiple Plots
Creating Subplots
Adding multiple plots
Grid and Complex Layouts

Seaborn

Understanding Seaborn Library
Default Statistical Plots
Line Plot, Scatter Plot, Bar Plot,
Histograms, Box
Plots, Violin Plots, Heatmaps etc.
Customized Plots
Categorical Data Plotting
Distribution Plots
Dist Plots
Kernel Distribution estimators plots (KDE)
Regression Plots

Plotly

Concept of Plotly
Understanding Plotly with its benifits
Plots using Plotlu
Line, Scatter, Bar plot, Pir Chart,
Heatmaps, Area
Charts etc.
3D Plots with Plotly
3D Scatter Plos,
3D Line charts
Annotations and Text Addition
Geographical Plotting with Plotly
Visualization with Maps
Geo Spatial Data Mapping

Capstone Project For Data Analytics

There will be at least 10 Data Analytics Capstone Projects available according to the different industries:

BFSI - 2
FMCG - 2
Healthcare - 2
Automobile - 2
Entertainment - 2

Capstone Project For Data Analytics

There will be at least 10 Data Analytics Capstone Projects available according to the different industries:

BFSI - 2
FMCG - 2
Healthcare - 2
Automobile - 2
Entertainment - 2

My Sql (SEQUEL)

Introduction to Databases and SQL

What is a database?
Introduction to SQL (Structured Query Language)
Key database concepts (tables, rows, columns)
Setting up MySQL (or MySQL Workbench)
Basic SQL queries (SELECT, FROM, WHERE)

Data Retrieval With SQL

Inserting data into tables (INSERT INTO)
Updating existing data (UPDATE)
Deleting data (DELETE FROM)
Creating and modifying tables (CREATE TABLE, ALTER TABLE)

Data Aggregation And Grouping

Aggregating data using functions (SUM, AVG, COUNT, etc.)
GROUP BY clause for data grouping
HAVING clause for filtering grouped data

Data Joins And Relationships

Understanding table relationships (foreign keys}
INNER JOIN, LEFT JOIN, RIGHT JOIN
Using subqueries for complex queries

Power Bl

Introduction to Power Bl and Data Sources

Overview of Power Bl and its components
Installing Power Bl Desktop
Connecting to various data sources (Excel, databases, web data, etc.}
Loading and transforming data in the Power Query Editor

Data Modeling in Power Bl

Introduction to data modeling concepts
Creating relationships between tables
DAX (Data Analysis Expressions} basics
Measures and calculated columns

Data Visualization with Power Bl

Creating different types of visualizations (bar charts, line charts, pie charts, etc.}
Customizing visual elements (colors, fonts, titles}
Interactivity with slicers and filters
Drill-through and drill-down

Power Bl for Reports and Dashboards