PG Certification Program in Data
Science and Analytics

Data Science Course-13

Launch your career with a 100% Job
Guarantee Pay After Placement Program

09 Month | Weakened Live Classes | Guaranteed Placement | Mentorship and Mock Interview

Next Cohort Starts: 31st October 2023

Minimum Eligibility: Bachelor’s Degree with minimum 50% or equivalent passing marks. No coding experience required.

Learning Format: Online Bootcamp

Get Placed in

9/10 of our learners got placement with salary hike of 200% and achieve their outcomes.

Tools Covered

Live Online Classes

Learn through live online lectures delivered by our Top Ranked Faculty (after working hours)

Hands on learning

Become future ready by applying what you will learn and built real-life projects.

ISIEINDIA Certificate

Earn a PG Certificate in Data Science from ISIEINDIA - Ranked #1 in Analytics Education.

Placement Guaranteed

5 Guarantee job interview from over 350+ Hiring Partner.

Placement Highlights

5 Guaranteed Interview with Top Organizations

Data Science Course-07

350+

Participating Companies

Data Science Course-08

6.9 LPA

Average CTC

Data Science Course-09

30 LPA

Highest CTC

Data Science Course-10

60 %

Average Salary Hike

Top Skills You Will Learn

Predictive Analytics using Python, Machine Learning, Data Visualization, Big Data, Natural Language Processing

Who Is This Programme For?

Engineers, Marketing & Sales Professionals, Freshers, Domain Experts, Software & IT Professionals.

Job Opportunities

Data Analyst, Data Scientist, Data Engineer, Product Analyst, Machine Learning Engineer, Decision Scientist

Minimum Eligibility

Bachelor’s Degree with minimum 50% or equivalent passing marks. No coding experience required.

What are the latest trends in Data Science ?

Data Analyst

Understand the issues and
create models based on the
data gathered, and also manage
a team of Data Analyst.

Data Scientist

Build strategies on frameworks
and technologies to develop
solutions and help the
organization prosper.

Data Engineer

With the help of several
Learning tools and technologies,
build statistical models with
huge chunks of business data.

Applied Scientist

Design and build Machine Learning
models to derive intelligence for the
numerous services and products
offered by the organization.

Big Data Specialist

Create and manage pluggable
service-based frameworks that
are customized in order to import,
cleanse, transform, and validate data.

Senior Business Analyst

Extract data from the respective
sources to perform business
analysis, and generate reports,
dashboards, and metrics.

Still have Questions?

Talk to our Experts…

Get Ahead with ISIEINDIA's Master Certificate

Earn your Data Scientist course certificate
Our Data Science course is exhaustive and this certificate is proof that you have taken a big leap in mastering the domain.

Differentiate yourself with a Masters Certificate
The knowledge and Data Science skills you’ve gained working on projects, simulations, case studies will set you ahead of the competition.

Syllabus

Best-in-class content by leading faculty and industry leaders in the form of videos, cases and projects, assignments and live sessions

150+

Content Hours Available

20+

Industry Projects

60+

Live Learning Sessions

14+

Programming Tools/ Languages

Module 1

Flowchart

Data

Types

Operators

Conditional Statements

Loops

Functions & Recursions

Strings

In-built Data Structures- List

Tuple

Dictionary

Set

Practice

Python Refresher

Lambda Functions

List Comprehension

Functional Programming

Decorator

Args

Kwargs

Object Oriented Programming

Exception Handling

Modules

Package

Library

Built-in Modules in Python

Basic DSA & Problem Solving

Numpy

Pandas

Data Visualisation using Matplotlib & Seaborn

Regular Expression/ Pattern Matching

Git and Github (Recorded Session)

Probability Theory & Descriptive Statistics

Probability Distributions Inferential Statistics

Coordinate Geometry

Linear Algebra

LP Optimization Basics

Estimation Problems

Module 2

Databases & SQL

Web API

Scraping

Data Cleaning

Unstructured Data

Hypothesis Testing

Parametric vs non-parametric

Z-test

Chi-square

Skewness

Kurtosis

Normality Test

Experiment Design

ANOVA

Simulations

Power of Test

A/B testing

Diff n Diff

Multi-arm Bandits

EDA

Covariance

Correlation

Pearson

Spearman Rank

Multi-dimensional

Feature Engineering

Column normalisation

Standardisation

Covariance Matrix

Missing Values

Outlier Treatment

Module 3

Managing Data Sources & Visualizations

Analysing Data using Statistical Tools

Creating Basic Charts

Dashboards & Action

Metric Design

Decode Product & Strategy Rounds

Advanced SQL

Google Spreadsheets

Introduction to Excel and Formulas

Tables

Chart and Statistical Functions. Advanced Tableau

Mapping Geographic Data Using stories to build dashboards

Working with Times and Dates

Creating Conditional Calculations Using Logical Functions

Creating Level of Detail (LOD) Expressions

Summarising Data Using Table Calculations

Managing Text Strings

Module 4

Supervised Learning

Linear Regression

Gradient Descent

Multicollinearity

VIF

R-square

Heteroscedasticity

Sklearn

Polynomial Regression

Bias-Variance trade-off

Regularisation

Logistic Regression

Squashing function

AUC

ROC

Precision-Recall Curve

Confusion matrix

Specificity

KNN

Decision Trees

Ensemble learning

Bagging

Boosting

SHAP Values

Support Vector Machine

Bayesian Machine Learning

Managing Data Sources & Visualizations

Collaborative/Content filtering

Propensity analysis

Cold start problem Market Basket Analysis/Data

Mining/Association Mining

EDA

Resampling

Autocorrelation

Forecasting

Seasonal Naive

Double/Triple Exponential (Holt) Residual Analysis

Stationarity tests

Autoregressive methods

Moving average

ARIMA

SARIMA

Module 5

Linear Algebra - Vector and Matrices, Dot product, Projections, System of Equations, Matrix Transformation, Eigen Vectors and Values, Orthonormal Basis Vectors, SVD, PCA

Coordinate Geometry - Line, Plane, Hyper Plane, Half space, Classification using plane

Calculus - Functions, Limits, Derivatives, Partial derivatives, Saddle points

Linear Regression

Gradient Descent

Multicollinearity

VIF

R-square

Heteroscedasticity

Sklearn

Polynomial Regression

Bias-Variance trade-off

Regularisation

Logistic Regression

Squashing function

AUC

ROC

Precision-Recall Curve

Confusion matrix

Specificity

KNN

Decision Trees

Ensemble learning

Bagging

Boosting

SHAP Values

Support Vector Machine

Bayesian Machine Learning

KMeans

Customer Segmentation

Hierarchical

DBSCAN

Anomaly Detection

Local Outlier Factor

Isolation Forest

Dimensionality Reduction

PCA

t-SNE

GMM

Information Theory

Expectation Maximization

Collaborative/Content filtering

Propensity analysis

Cold start problem

EDA

Resampling

Autocorrelation

Forecasting

Seasonal Naive

Double/Triple Exponential (Holt) Residual Analysis

Stationarity tests

Autoregressive methods

Moving Average

ARIMA

SARIMA

Neural Networks - MLP

Backpropagation

Hyperparameter Tuning

Practical Aspects of DL

Keras

Tensorflow

Join the Data Science industry

By 2026, IDC predicts Data Science and cognitive computing spending will reach $52.2 billion. Data Scientist is one of the hottest professions.

Data Science Course-10

28%

Annual Job Growth By 2026

Data Science Course-08

11.5 M

Expected New Jobs By 2026

Data Science Course-09

Rs.4.5L -22L

Average Annual Salary

Source: Market Research Rpt

Source: US bureau of Labor

Source: Glassdoor

Companies hire Data Scientists

and many more…

Batch Profile

The Data science certification program is designed for working individuals from various sectors. The variety of students enriches class discussions and interactions.

Admission Details

Admission Details

Candidates can apply to this Data Science certification program in 3 steps. Selected candidates receive an offer of admission, which is accepted by admission fee payment.

STEP 1

Data Science Course-47

Submit Application

Tell us about yourself and why you want to do a Data Science certification

STEP 2

Data Science Course-48

Application Review

An admission panel will shortlist candidates based on their application

STEP 3

Data Science Course-49

Admission

Selected candidates can start the Data Science program within 1-2 weeks

Admission Fee & Financing

The admission fee for this Data Science program is ₹ 1,49,999 (Incl. taxes). This fee covers applicable program charges and NSDC Certification.

Financing Options

We are dedicated to making our programs accessible. We are committed to helping you find a way to budget for this program and offer a variety of financing options to make it more economical.

No Cost EMI

We have partnered with the following financing
companies to provide competitive finance options
at 0% interest rate with no hidden costs.

Financing as low as

₹ 8,333/month*

Other Financing Options

We provide the following options for one-time payment

Data Science Course-53

Internet
Banking

Data Science Course-54

Credit/Debit
Card

Data Science Course-55

Standard
EMI

Total Admission Fees

₹ 1,49,999

(Incl. taxes)

Student Testimonial’s

Open chat
Hello 👋
Can we help you?