Call WhatsApp Enquiry

Full Stack Data Science & Artificial Intelligence Course

For Tech Lead, Team Lead, Managers

Our course is best suited for professionals
looking to change their current domain and start a New Career in Data Science and Artificial Intelligence in senior and leadership roles.

Course Fee

79000
11 months (300+ hrs)
This course includes:

Weekend and Weekdays Batches

15+ Real World Industry Project

From Basics to Advance

 Guaranteed Job Referrals

 Special Classes for non-programmers

Live Faculty-led Online Training

One & half Year Flexible Subscription

Eligibility

8+ yrs work exp.

Certification

Accredited with IBM

Projects

15+ Real Time Projects

No Cost EMI

₹ 8.5k/mon*(9 mon*)

ABOUT COURSE
About This Program

Eligibility

Best for Senior Professional, Tech Lead, Team Lead, Managers, and Leaders having 8+ years of experience.

Job Assistance

Resume sessions, Mock interviews, and job referrals to land your dream job or data science and data scientist manager.

Live Projects

15+ Real-time projects from multiple domains like healthcare, BFSI, retail, manufacturing, e-commerce, and marketing.

Full Stack Data Science & Artificial Intelligence Course

For Tech Lead, Team Lead,Managers

Our course is best suited for professionals looking to change their current domain and start a New Career in Data Science and Artificial Intelligence in senior and leadership roles.

Course Fee

79000
11 months (300+ hrs)
This course includes:

Weekend and Weekdays Batches

15+ Real World Industry Project

From Basics to Advance

 Guaranteed Job Referrals

 Special Classes for non-programmers

Live Faculty-led Online Training

One & half Year Flexible Subscription

Eligibility

8+ yrs work exp.

Certification

Accredited with IBM

Projects

15+ Real Time Projects

No Cost EMI

₹ 8.5k/mon*(9 mon*)

ABOUT COURSE
About This Program

Eligibility

Best for Senior Professional, Tech Lead, Team Lead, Managers, and Leaders having 8+ years of experience.

Job Assistance

Resume sessions, Mock interviews, and job referrals to land your dream job or data science and data scientist manager.

Live Projects

15+ Real-time projects from multiple domains like healthcare, BFSI, retail, manufacturing, e-commerce, and marketing.
Key Highlights
Program Overview

  Designed for Senior Managers & Leaders

  Real-Time Use Cases from Multiple Domains

  Industrial Certificate which is accredited with IBM

  One-on-One with Industry Mentors

  Guaranteed Job Referrals For Working Professionals

  Interview Prep Session And Mock Interview

  Industry Accredited Global Certification Course

  15+ Real Time Project from BFSI, Retail, Healthcare

  Special Classes For Non-Programming Background

   Interest Free Loan and No Cost EMI on Credit cards

Key Highlights
Program Overview

  Designed for Senior Managers & Leaders

  Real-Time Use Cases from Multiple Domains

  Industrial Certificate which is accredited with IBM

  One-on-One with Industry Mentors

  Guaranteed Job Referrals For Working Professionals

  Interview Prep Session And Mock Interview

  Industry Accredited Global Certification Course

  15+ Real Time Project from BFSI, Retail, Healthcare

  Special Classes For Non-Programming Background

   Interest Free Loan and No Cost EMI on Credit cards

TOP SKILLS
Top Skills You Will Learn

Top Skills You Will Learn

Python, Statistics, ML, Tensorflow, NLP, R, Apache Spark, MySQL, Power BI, Tableau, Hadoop, Cloud Deployment, Project Management in Data Science and AI, Domain Training in BFSI, HR, Retail, etc.

Job Opportunities

Data Analyst manager,Data Scientist, Data Engineer, Product Analyst, Machine Learning Engineer, Decision Scientist, data scientist manager.

Details About Real Time Projects.

3 Capstone Project and 15+ Real-time projects from multiple domains help you to showcase practical skills to the recruiter and get your dream job.

Minimum Eligibility

The course is specially designed for business leaders, project managers, Tech Lead, Team Lead, Managers having 8+ years of experience in any domain.
TOP SKILLS
Top Skills You Will Learn

Top Skills You Will Learn

Python, Statistics, ML, Tensorflow, NLP, R, Apache Spark, MySQL, Power BI, Tableau, Hadoop, Cloud Deployment, Project Management in Data Science and AI, Domain Training in BFSI, HR, Retail, etc.

Job Opportunities

Data Analyst manager,Data Scientist, Data Engineer, Product Analyst, Machine Learning Engineer, Decision Scientist, data scientist manager.

Details About Real Time Projects.

3 Capstone Project and 15+ Real-time projects from multiple domains help you to showcase practical skills to the recruiter and get your dream job.

Minimum Eligibility

The course is specially designed for business leaders, project managers, Tech Lead, Team Lead, Managers having 8+ years of experience in any domain.

Download Program Brochure

FEATURES
Course Features
Course Prerequisite

There is no Prerequisite for this course as we cover programming and statistics from basics. We provide special classes & support for professionals from non-programming / non-technical backgrounds.

Special Support to Non Programmers

we provide special Python programming fundamentals classes designed for non-programmers and non-technical domain professionals which helps you to learn programming concepts easily.

Program Eligibility

Work Experience :

  • Professionals working as project managers and team leads with 8 to 15 years of experience in any domain (technical or non technical) Work.

To know which Program is best suitable for your profile, Apply for Career counselling   session with our expert.

Who Should Apply
  • Team managers, Project managers, Technical lead, professionals having 8 to 15 years of work exp. looking to start their career in data science & analytics manager.
  • Have a good understanding of any programming language(Working knowledge)
    Good understanding in mathematics.

To know which Program is best suitable for your profile, Apply for a Career counseling session with our expert.

About Instructors
  • Our instructors are working professionals who graduated from premier institutes like BITS Pilani, IIT Roorkee, and working in companies as Data Scientist/Machine Learning Engineer and Artificial Intelligence expert.
  • Students will be guided by our mentors until the end of a course. A student can seek help by our mentors even after course completion for knowledge and placement purposes.
Fees and Duration
Weekday Program Batches: 9 Months

Monday – Friday – 2 hours every day

Weekend Batches: 11 Months

Saturday & Sunday – 4 hours every day

Program Fee: Rs. 79,000/-

INTEREST-FREE INSTANT LOAN WITHOUT CREDIT CARD

NO COST EMI ON MAJOR CREDIT CARDS

Hybrid Model Classes

Attain 2 Capstone & 12+ Real Time AI and ML Projects in Classroom-mode OR Live-online led by industrial experts.
Locations: Pune, Mumbai, Delhi, Hyderabad, Chennai, Bengaluru

It is completely optional to attain project sessions in classroom. You can also prefer Live-Online Interactive Mode guided by Industrial Expert.

COURSE
Syllabus

Introduction to Programming 3hr

What is a programming language ? Source code Vs bytecode Vs machine code
Compiler Vs Interpreter ,C/C++, Java Vs Python

Jupyter notebook basics 1hr

Different type of code editors in python introduction to Anaconda and
jupyter notebookFlavours of python.

Python Programming Basics 2hr

Variable Vs identifiers Vs strings, Operators Vs operand Procedure
oriented Vs modular programming

Statistics basics 2hr

Introduction to statisticsMean,median, mode, Standard deviation,
AverageIntroduction to probability,permutations and
combinationsIntroduction to linear Algebra

Git and GitHub 2hr

Learn the key concepts of the Git source control system,Configure SSH for authentication,Create and use a remote repository on GitHub,Git Overview

Tools Covered

Programming Basics &Environment Setup hr

Installing Anaconda, Anaconda, Basics, and Introduction, Get familiar with version control, Git, and GitHub.Intro to Jupyter Notebook environment. Basics Jupyter notebook Commands.Programming language basics.

Python Programming Overview hr

Python 2.7 vs Python 3,Writing your First Python Program
Lines and Indentation,Python Identifiers,Various Operators and Operators
Precedence ,Getting input from User,Comments,Multi line Comments.

Strings, Decisions And Loop
Control
hr

Working With Numbers, Booleans and Strings,String types and
formatting, String operations Simple if Statement, if-else Statement
if-elif Statement. Introduction to while Loops. Introduction to for Loops,Using
continue and break.

Python Data Types hr

List,Tuples,Dictionaries,Python Lists,Tuples,Dictionaries,Accessing Values,Basic Operations,Indexing, Slicing, and Matrixes,Built-in Functions & Methods,Exercises on List,Tuples And Dictionary

Functions And Modules hr

Introduction To Functions – Why Defining Functions. Calling Functions
Functions With Multiple Arguments.Anonymous Functions – Lambda
Using Built-In Modules, User-Defined, Modules, Module Namespaces,Iterators And Generators

File I/O And Exceptional Handling and Regular Expression hr

Opening and Closing Files,open Function,file Object Attributes
close() Method ,Read,write,seek.Exception Handling, try-finally Clause
Raising Exceptions, User-Defined Exceptions. Regular Expression- Search
and Replace. Regular Expression Modifiers. Regular Expression Patterns,re module.

Data Analysis Using Numpy And
Pandas
hr

Introduction to Numpy. Array Creation, Printing Arrays, Indexing, Slicing and Iterating, Shape Manipulation -Changing the shape, stacking, and splitting of the array. Vector stacking, Broadcasting.

Pandas : Introduction to Pandas,Importing data into Python
Pandas Data Frames, Indexing Data Frames, Basic Operations With Data frame,
Renaming Columns, Subletting, and filtering a data frame.

Data Visualisation using Python:
Matplotlib and Seaborn
hr

Matplotlib: Introduction,plot(),Controlling Line Properties,Subplot with Functional Method, MUltiple Plot, Working with Multiple Figures,Histograms

Seaborn :Intro to Seaborn And Visualizing, statistical relationships , Import and Prepare data.Plotting with categorical data and Visualizing linear relationships Seaborn Exercise

Tools Covered

Fundamentals of Math and
Probability
hr

Basic understanding of linear algebra,Matrics, vectors. Addition and
Multimplication of matrics.Fundamentals of Probability
Probability distributed function and cumulative distributed function.

Descriptive Statistics hr

Describe or sumarise a set of data Measure of central tendency and
measure of dispersion.The mean,median,mode, curtosis and skewness. Computing Standard deviation and Variance.Types of distribution.

Inferential Statistics hr

What is inferential statistics,Different types of Sampling techniques
Central Limit Theorem,Point estimate and Interval estimate
Creating confidence interval for,population parameter
Characteristics of Z-distribution and T-,Distribution. Basics of Hypothesis
Testing. Type of test and rejection,region. Type of errors in Hypothesis yesting,

Hypothesis Testing hr

Hypothesis Testing Basics of Hypothesis Testing ,Type of test and Rejection Region,Type o errors-Type 1 Errors,Type 2,Errors. P value method,Z score
Method. The Chi-Square Test of, Independence.Regression. Factorial Analysis of
Variance. Pearson Correlation, Coefficients in Depth. Statistical,Significance, Effect Size

Data Processing & Exploratory
Data Analysis
hr

What is Data Wrangling, Data Pre-processing and cleaning?
How to Restructure the data? What is Data Integration and Transformation

Introduction To Machine Learning 8hr

What is Machine Learning? What is the Challenge?
Introduction to Supervised Learning, Introduction to Unsupervised
Learning, What is Reinforcement Learning? Machine Learning applications
Difference between Machine Learning and Deep Learning

Supervised Learning 8hr

Support Vector Machines,Linear regression,Logistic regression
Naive Bayes, Linear discriminant analysis, Decision tree
the k-nearest neighbor algorithm, Neural Networks (Multilayer perception) Similarity learning

Linear Regression 8hr

Introduction to Linear Regression,Linear Regression with Multiple
Variables, Disadvantage of Linear Models, Interpretation of Model Outputs
Understanding Covariance and Colinearity, Understanding Heteroscedasticity

Case Study – Application of Linear Regression for Housing
Price Prediction

Logistic Regression hr

Introduction to Logistic Regression.–Why Logistic Regression .
Introduce the notion of classification, The cost function for logistic regression
Application of logistic regression to multi-class classification.
Confusion Matrix, Odd’s Ratio, And ROC Curve
Advantages And Disadvantages of Logistic Regression.

Decision Trees hr

Decision Tree – data set How to build decision tree? Understanding Kart Model
Classification Rules- Overfitting Problem. Stopping Criteria And Pruning. How to Find the final size of Trees? Model A decision Tree.
Naive Bayes. Random Forests and Support Vector Machines.Interpretation of Model Outputs

Unsupervised Learning hr

Hierarchical Clustering k-Means algorithm for clustering –groupings of unlabeled data points.Principal Component Analysis(PCA)-Data. Independent components analysis(ICA) Anomaly Detection Recommender System-collaborative
filtering algorithm

Case Study– Recommendation
Engine for e-commerce/retail chain

Natural language Processing hr

Introduction to natural Language Processing(NLP).
Word Frequency Algorithms for NLP Sentiment Analysis

Case Study :Twitter data analysis using NLP

Introduction to Time Series Forecasting hr

Basics of Time Series Analysis and Forecasting ,Method Selection in Forecasting,Moving Average (MA) Forecast Example,Different Components of
Time Series Data, Log Based Differencing, Linear Regression For Detrending

ARIMA and Multivariate Time
Series Analysis
hr

Introduction to ARIMA Models,ARIMA Model Calculations,Manual ARIMA
Parameter Selection,ARIMA with Explanatory Variables Understanding Multivariate Time Series and Their Structure,Checking for Stationarity and Differencing the MTS

Case Study : Performing Time Series
Analysis on Stock Prices

Introduction to Deep Learning And Tensor Flow hr

Neural Network Understaing Neural Network Model Installing TensorFlow Simple Computation ,Contants And Variables. Types of file formats in TensorFlow. Creatting A Graph –Graph Visualization. Creating a Model– Logistic Regression Model Building using tensor flow TensorFlow Classification Examples

Introduction to Tensor Flow hr

Installing TensorFlow Simple Computation,Contents And Variables Types of file formats in TensorFlow Creatting A Graph – Graph Visualization Creating a Model – Logistic Regression Model Building TensorFlow Classification Examples

Understanding Neural Networks With Tensor Flow hr

Basic Neural Network, Single Hidden Layer Model,Multiple Hidden Layer Model,Backpropagation – Learning,Algorithm and visual representation,
Understand Backpropagation – Using Neural Network Example TensorBoard
Project on backpropagation

Convolutional Neural Network(CNN) hr

Convolutional Layer Motivation ,Convolutional Layer Application,
The architecture of a CNN, Pooling Layer Application Deep CNN, Understanding and Visualizing a CNN,Project: Building a CNN for Image Classification

Introduction to NLP & Text Analytics hr

Introduction to Text Analytics, Introduction to NLP
What is Natural Language Processing?, What Can Developers Use NLP Algorithms For?

NLP Libraries. Need of Textual Analytics Applications of Natural Language
Procession
,Word Frequency Algorithms for NLP Sentiment Analysis

Text Pre Processing Techniques hr

Need of Pre-Processing Various methods to Process the Text
data Tokenization ,Challenges in Tokenization,Stopping ,Stop Word Removal
Stemming – Errors in Stemming,Types of Stemming Algorithms -Table
lookup Approach ,N-Gram Stemmers

Distance Algorithms used in Text Analytics hr

string Similarity,Cosine Similarity Mechanishm -Similarity between Two text
documents. Levenshtein distance -measuring the difference between two sequences. Applications of Levenshtein distance LCS (Longest Common Sequence ) Problems and solutions ,LCS Algorithms

Information Retrieval Systems hr

Information Retrieval -Precision,Recall,F- score,TF-IDF,KNN for document retrieval,K-Means for document retrieval,Clustering for document retrieval

Topic Modelling & Dirchlett Distributions hr

Introduction to Topic Modelling,Latent Dirchlett Allocation,Adavanced Text Analytics & NLP,Introduction to Natural Language,Toolkit,POS Tagging NER

Projects And Case Studies hr

a. Sentiment analysis for twitter, web
articles
b. Movie Review Prediction
c. Summarization of Restaurant
Reviews

RDBMS And SQL Operations hr

Introduction To RDBMS. Single Table,Queries – SELECT,WHERE,ORDER,BY,Distinct,And ,OR. Multiple Table
Queries: INNER, SELF, CROSS, and OUTER, Join, Left Join, Right Join, Full
Join, Union,Advance SQL Operations:Data Aggregations and summarizing the data
Ranking Functions: Top-N Analysis, Advanced SQL Queries for Analytics

NoSQL Databases hr

Topics – What is HBase? HBase Architecture, HBase,Components,Storage Model of HBase,HBase vs RDBMS,Introduction to Mongo DB, CRUD,Advantages of MongoDB over
RDBMS,Use cases

Programming with SQL hr

Mathematical Functions,Variables,Conditional Logic Loops,Custom Functions
Grouping and Ordering, Partitioning, Filtering Data, Subqueries

MongoDB Overview hr

Where MongoDB is used? MongoDB Structures,MongoDB Shell vs MongoDB Server
Data Formats in MongoDB,MongoDB Aggregation Framework,Aggregating Documents
What are MongoDB Drivers?

Basics and CRUD Operation hr

Databases, Collection & Documents,Shell & MongoDB drivers
What is JSON Data Create, Read, Update, Delete Finding, Deleting, Updating,
Inserting Elements Working with Arrays Understanding Schemas and Relations

Introduction to MongoDB hr

What is MongoDB?Characteristics and Features,MongoDB Ecosystem,Installation process Connecting to MongoDB database,Introduction to NoSQL
Introduction of MongoDB module,What are ObjectIds in MongoDb

Introduction To R hr

Installation Setup Quick guide to RStudio User Interface
RStudio’s GUI3 Changing the appearance in RStudio
Installing packages in R and using the library Development Environment Overview
Introduction to R basics Building blocks of R Core programming principles
Fundamentals of R

Programming with R hr

Creating an object,Data types in R,Coercion rules in R
Functions and arguments, Matrices, Data Frame, Data Inputs and Outputs with R, Vectors and Vector operation Advanced Visualization, Using the script vs. using the console

Manipulating Data hr

Data transformation with R – the Dplyr package – Part
Data transformation with R – the Dplyr package – Part
Sampling data with the Dplyr package,Using the pipe operator in R
Tidying data in R – gather() and separate(),Tidying data in R – unite() and
spread()

Visualizing Data hr

Intro to data visualization,Introduction to ggplot2
Building a histogram with ggplot2, Building a bar chart with ggplot2
Building a box and whiskers plot with ggplot2, Building a scatterplot with ggplot2

Introduction to Tableau hr

Connecting to data source Creating dashboard pages
How to create calculated columns,Different charts
Hands-on :Hands on on connecting data
source and data cleansing
Hands on various charts

Visual Analytics hr

Getting Started With Visual Analytics,Sorting and grouping Working with sets, set action,Filters: Ways to filter, Interactive Filters,Forecasting and Clustering
Hands-on: Hands on the deployment of Predictive
model in visualization

Dashboard and Stories hr

Working in Views with Dashboards and Stories,Working with Sheets
Fitting Sheets, Legends and Quick Filters, Tiled and Floating Layout Floating Objects

Mapping hr

Coordinate points,Plotting Latitude and Longitude
Custom Geocoding,Polygon Maps,WMS and Background Image

Getting Started With Power BI hr

Installing Power BI Desktop and Connecting to Data,Overview of the Workflow in Power BI Desktop,Introducing the Different Views of the Data Mode Query Editor Interface Working on Data Model

Programming with Power BI hr

Working with Timeseries,Understanding aggregation and granularity
Filters and Slicers in Power BI Maps, Scatterplots and BI Reports
Connecting Dataset with Power BI Creating a Customer Segmentation
Dashboard Analyzing the Customer Segmentation Dashboard

Introduction To Hadoop hr

Distributed Architecture – A Brief Overview Understanding Big Data,
Introduction To Hadoop ,Hadoop,Architecture,HDFS ,Overview of MapReduce
Framework,Hadoop Master – Slave Architecture,MapReduce Architecture
Use cases of MapReduce

Apache Spark Analytics hr

What is Spark Introduction to Spark RDD,Introduction to Spark SQL and Dataframes,Using R-Spark for machine learning
Hands-on:installation and configuration of Spark
Using R-Spark for machine learning
programming

Apache Spark Analytics hr

Getting to know PySpark,Pyspark Introduction,Pyspark Environment Setup
pySpark – Spark context,RDD , Broadcast and Accumulator,Sparkconf and Sparkfiles,Spark MLlib Overview,Algorithms and utilities in Spark
Mlib

Case Study hr

Hands-on:
Map-reduce Use Case 1: Youtube
data analysis
Map-reduce Use Case 2: Uber Data
Analytics
Hands-on: Spark RDD programming
Hands-on: Spark SQL and Dataframe programming

Introduction To GCP Cloud ML Engine hr

Introduction to Google CloudML Engine,CloudML Engine in Machine,Learning WorkFlow,+3Components of Cloud ML Engine -Google Cloud Platform Console.
gcloud command-line tool and Rest API
API

Training Machine Learning
Model
hr

Developing a training application Packaging a training application
Running and monitoring a training job Using hyperparameter tuning Using GPUs for training models in the cloud

Deploying Machine Learning Model hr

Deploying Models ,Understanding training graphs and serving graphs,
Check and adjust model size Build an optimal prediction graph Creating input function creating a model version Getting Online Prediction

Building AI-ML and Analytics
capabilities in organisation/Projects
6 hr

Use data science and AI to create and implement business strategies.
Incorporate AI on top of existing products and services. Understand the
requirements of clients and projects using data driven-methods and perspective.
Transform business problems to data analytics problems. Improve organization
processes using analytics.

Building a data science and AI Team
6hr

Defining the data science team, Various job roles in data science – Data analyst, data engineer, data scientist, ML engineer, data science manager. Understand the qualification and expertise of these job roles. Interviewing process for data science job positions. On-boarding the Data Science Team, working with other teams and stakeholders. Challenges and difficulties.

Case Study 1: Strategy for implementing ML in web-based retail product (existing project)
Case study 2: Convert a business problem to a data problem from scratch
(BFSI domain)
Capstone Project-3 : Deliver a machine learning and AI Project from scratch starting from strategy, planning, team building, modeling and deployment. You will be assigned 4 machine learning engineers and you need to deliver this project under mentorship of our expert in 3 months time.

Understanding the data science workflow and Pipeline6 hr

Organize a data science project workflow from scratch, workflow of a
data science project, Identifying various data sources, Cleaning your data, EDA, creating ML model, Model deployment, Monitoring. Building data
pipelines, Type of data, evolution of pipelines.

Managing data science Projects6 hr

Determine Business Objectives,Determine Data Mining Goal, Understand
data, Verify Quality of data,Getting familiar with CRISP-DM methods and
process, Business understanding, Data understanding, data preparation,modeling, evaluation, Deployment.

Case study : Solve a retail business problem and follow CRISP-DM process and methods.

Architecture of AI & ML Systems6 hr

Strategy for building artificial intelligence systems for business.
Understand AI infrastructure requirements, the Importance of machine
learning system architectures, and their various components. Build a machine learning system architectures for a chat-bot, recommended systems, etc.

Case Study/Practice: Live interview of 2 candidates for data analyst and
ML engineer Job Roles.

Banking & Finance analytics Domain6 hr

Retail Sector4 hr

Healthcare domain4 hr

E-Commerce Domain
4 hr

Supply Chain Management
4 hr

Manufacturing Domain
3 hr

Automotive Domain
3 hr

Project : Loan Default Prediction

The bank wants to improve its services by finding interesting
groups of clients. Fortunately, the bank stores data about their clients, the accounts(transactions within several months), the loans already granted, the credit cards issued. This process of loan default prediction can be done with machine learning algorithms.

Project : Analyzing Health Data and
tracking human activity

The goal is to breakdown all the data that the Samsung Health app has collected and see what useful insights we can gain by analyzing it.

Project : IBM HR Analytics

Applying analytic processes to the human resource department of an organization in the hope of improving employee performance and therefore getting a better return on investment. This is especially concerning if your business is customer-facing, as customers often prefer to interact with familiar people.

Project : Clustering Customers

Big Bazaar has retail outlets across major metropolitan cities in India.
With the help of machine learning algorithms, we can better understand
customer behavior and understand their buying needs better.BigBazaar runs various loyalty programs, festive offers which provide their customer more
opportunities to avail discounts.

Project : Identify fraudulent credit card transactions

To recognize fraudulent credit card transactions so that customers are not charged for items that they did not purchase. It involves various
processes like Data Cleaning, Data Visualization, Insights generation, Model generation, Feature Engineering, and so on.

Project : Consumer Reviews of
Amazon Products

The goal is to analyze Amazon’s most successful consumer electronics product launches; discover insights into consumer reviews and assist with machine learning models. What are the most reviewed Amazon products?
How do the reviews in the first 90 days after a product launch?

Project :Airbnb New User Bookings

The goal is to predict which country a new user’s first booking destination will be. By accurately predicting where a new user will book their first travel experience, Airbnb can share more personalized content with their community, decrease the average time to first booking, and better forecast demand.

Project :Netflix Movies and TV Shows

Explore what all other insights can be obtained from the list of tv
shows and movies available on Netflix as of 2019. Understanding what content is available in different countries. Identifying similar content by matching text-
based features. Network analysis of Actors / Directors and find interesting insights.

Project :Sales Forecasting

This dataset contains the sales for each department from the Walmart dataset containing data of 45 Walmart stores, selected holiday markdown events are
also included. These markdowns are known to affect sales, but it is challenging to predict which departments are affected and the extent of the impact.

Project :-BMW Pricing Challenge

To find a good statistical model to describe the value of a used
car depending on the basic description How does the estimated value
of a car change over time? Can you detect any patterns? How big is the influence of the factors not represented in the data on the price?

Project :-Bosch Production Line Performance

To predict internal failures using thousands of measurements and
tests made for each component along the assembly line. This would enable Bosch to bring quality products at lower costs to the end-user.The goal is to predict which parts will fail quality control

Project :-Trending YouTube Video Statistics

The dataset of this project are a daily record of the top trending YouTube
videos, to generate insights like Sentiment analysis in a variety of forms
Categorizing YouTube videos based on their comments and statistics
Training ML algorithms like RNNs to generate their own YouTube comments.

Project :-Generating Chatbot

In this project we will build a simple retrieval based chatbot based on NLTK
library in python, to perform tasks such as automatic summarization, translation, named entity recognition, relationship extraction, sentiment analysis, speech recognition, and topic segmentation.

Project :-Identify And Predict Customer churn in telecom industry

The goal is to develop a churn prediction model that assists telecom operators to predict customers who are most likely subject to churn. Also to understand the customer behavior and reasons for churn. Apply multiple
classification models to predict customer churn in the telecom industry.

Project :-Smart Supply Chain for Big Data Analysis

A DataSet of Supply Chains used by the company DataCo Global is
used for the analysis. Dataset of Supply Chain, which allows the
use of Machine Learning Algorithms and R Software.It also allows the correlation of Structured Data with Unstructured Data for knowledge generation.

300+

Content Hours Available

15+

Industry Projects

20+

Live Learning Sessions

25

Expert Coaching Sessions

14

Programming Tools/ Languages
MODULES
Course Modules

Python for Data Science

Statistics Mathematics

Machine Learning

Deep Learning

NLP / Text Analytics

Computer Vision

Project Management

R Programming

Domain Training

Google Cloud

mySQL

Mongo DB

Power BI

Tableau

Apache Spark

Reinforcement Learning

Real Time Projects

AI/ML Project Management

MODULES
Course Modules

Python for Data Science

Statistics Mathematics

Machine Learning

Deep Learning

NLP / Text Analytics

Computer Vision

Project Management

R Programming

Domain Training

Google Cloud

mySQL

Mongo DB

Power BI

Tableau

Apache Spark

Reinforcement Learning

Real Time Projects

AI/ML Project Management

Program Schedule
For Managers and Leaders

Module 0: Special Sessions For Non-Programmers

 Time duration: 4 days (8 hours)
 One Week before your Batch Starts

We believe that professionals coming from non-programming backgrounds need special assistance and support. we provide special programming fundamentals classes designed for non programmers and non technical domain professionals which helps you to learn programming concepts easily.

Term 1: Python For Data Science

 Time duration: 5 Weeks (40 hours)
 1.5 Months

Python is one of the most commonly used programming languages in the field, in this section, we start Basic python & Environment Setup and advanced Python scripts such as List, Tuples, Dictionaries, File Operations, Regular Expressions, dealing with binary data, and using the extensive Python module features. Python libraries and tools,Numpy ,Pandas,Matplotlib and Seaborn etc

Term 2: Statistics And Machine Learning,Capstone Project 1 – ML

 Time duration: 9 Weeks (72 hours)
 2 Months

Statistics are the use of mathematics to conduct technical predictive analytics, IN statistics covering math and probability fundamentals, hypothesis testing, data processing, and exploratory data analysis, etc. Machine learning curriculum that will provide you to learn techniques such as supervised learning, unsupervised learning, and natural language processing, etc.

Term 3: TensorFlow, Deep Learning, NLP & Text Analytics, Capstone Project 2 -NLP

 Time duration: 6 Weeks ( 48 hours)
 2 Months

TensorFlow is a platform built by Google. Deep Learning is a machine learning category. TensorFlow and deep learning cover topics such as Neural Network Model, Graph Visualization, Logistic Regression, CNN Architecture, Deep CNN Pooling Layer Application, etc.

Term 4: SQL,MongoDB,Tableau,Power BI,Big Data ,Spark Analytics,R And GCP

 Time duration:9 Weeks (72 hours)
 2 Months

Power BI and Tableau is the data visualization and business intelligence tool. Big data is the data sets that are so voluminous and complex that traditional data processing application software is inadequate to deal with them. Topics in Big data you must cover that is- Hadoop, MapReduce, Hive, Sqoop, Spark e.t.c.

Term 5 :Project Life Cycle, Domain Knowledge & Capstone project

 Time duration:8 Weeks (60 hours)
 1.5 Months
Each step in the lifecycle of data science projects depends on different skills and tools. Awareness of the industrial scenario,domain knowledge would allow professionals working in this sector to understand the real-world scenario and the specific problems of the industry

Projects And Job Assistance

 Integrated with the curriculum
 When: After every module

Candidates Effective completion of Term 1, Term 2, and Term 3, become eligible for the Career Assistance Program, In this programmer, we have offered Interview Prep Session & Mock Interview, Participating in Live Kaggle Competitions. Guaranteed Career References for Data Science/ML positions of an engineer.
Take part in guided workshops from various domains for real-time projects and get project support/mentorship from expert instructors.

SAMPLE CERTIFICATE

Global Accreditation and Certification

In Collaboration With IBM

Our Data Science & AI Certification Program helps you to start your career in data science and AI.

Enhancing your profile

Add this globally recognized certificate to uplift your profile and stand out of the crowd.

Real Time Project & Job Assurance

Course features 12+ Real time industry projects which can be added as a learning experience in your profile with 100% Interview Guarantee.
SAMPLE CERTIFICATE

Global Accreditation and Certification

In Collaboration With IBM

Our Data Science & AI Certification Program helps you to start your career in data science and AI.

Enhancing your profile

Add this globally recognized certificate to uplift your profile and stand out of the crowd.

Real Time Project & Job Assurance

Course features 12+ Real time industry projects which can be added as a learning experience in your profile with 100% Interview Guarantee.
TRANSITION STEPS
Learning Track

Step 1

Learn Full Stack DS & AI
Learn basics Python, Statistics, ML, NLP , DL, SQL and other modules in depth with real time case studies.

Step 2

Choose domain & get trained
You can select multiple domains and get trained based on your work experience, academics and career goal.

Step 3

Work on real time projects
Work on multiple real time industry projects and capstone from multiple domains with mentorship of our expert.

Step 4

Resume Prep & Mock Interview Session
Update your resume and practice mock interviews. Get 100% guaranteed job referrals for data scientist & ML Engineer.
DATA SCIENCE
Real Time Projects
DATA SCIENCE
Real Time Projects
FAQs
Frequently Asked Questions

What are the Prerequisites for data science certification Course?

There are no prerequisites for this course as all the modules are covered from basics and scratch. If you are from a non-technical and non-programming background, We provide special classes and assistance so that you can learn to program.

What if i miss few classes?What is flexi pass Option ?

In case you miss classes, You will be provided backup classes in other batches. If you miss more classes, You can request for batch change and join our next batch. To solve this issue, We provide a flexi-pass option for our data science course.

Those who enroll for live classroom training are eligible for a Flexi-pass of 6 months. With this option, We share your access to all ongoing batch details for a period of 6 months, so that you can attend live classroom sessions from any batches and learn at your own pace. This option also helps you to finish the course early as you can attend multiple batches simultaneously.
This option is best for someone working in shifts or needs to work on weekends sometimes.

What is the duration of this Course?

Duration Of this course is around 6 months, weekends only (4 hours on Sat and Sunday)
Course Duration: 200 hours (Approx)

The total duration of this course is 6 months but after 4 Months( once50% Of Machine learning is over) you can start working on Real-Time Projects and attend job interviews.

What is the mode of training?

We provide both options i.e Classroom training( in Marathahalli – Bangalore ) and instructor-led live training option. Based on your requirement and need, you can choose training mode.

How long will i get support for Job Assistance?

For 1 Year (After your course completion)

What is Job Readiness Program?

Job Readiness program helps you to prepare for data science interviews.

Resume Preparation Session: Expert guidance for writing a resume for data scientist Role

Preparing Project For interviews: Will help you to prepare and write a project description in your resume

Interview Guidance And Prep Session: 6 hours of interview readiness session to help you to prepare for interviews

One on One Mock Interviews

What is the eligibility for job assistance program?

You should have completed the course with

    • A minimum score of 70% in Assessment
    • Should have completed Assignments and case studies
    • Worked and successfully completed a min. the recommended number of real-time projects

Will i get referral for jobs?

Yes,We provide placement Assistance by referring your profile through our partnered consultancies and companies for relevant positions(Data Science/Data Analyst Roles).

Contact course manager/Counsellor to know the eligibility of job assistance program

Note: We don’t provide any 100% Job Guarantee

Can i Pay in installment?

There ai 0% EMI Available on Major credit cards.Please check with our sales team to know how 0% EMI on credit cards works.

Is there any discounts available ?What about group discounts?

We have promotions and early bird offer from time to time. Please check on the website or talk to our sales team to know more about the applicable discounts.

Group Discount: Group discount is applicable if you are joining with your friends.

  • 5% extra discount: Group of 2
  • 8% extra discount: Group of 3
  • Max 10% group discount: Group of 4+ members

How many minimum number of Projects should i work?

Number of Projects depends on your overall industry experience.Please find the recommended number of projects With industry experience.
2 yrs to 5 Yrs : 3 Projects
5 to 8 yrs: 5 Projects
8 yrs to 12 yrs: 7 + Projects
For your knowledge and practice, You can work on all the projects with us.
Contact our course expert to know more details
Note: Projects are guided by our expert industry mentors.

How many Real Time Projects will be covered in this Course?

There is a set of  12 Real-time projects from multiple domains like Banking, Finance, Insurance, Retail, Healthcare, and manufacturing. Based on your interest and domain, You can choose the project to work on.

Click here to download the list of project

How Projects Will be executed?

Your Project group will be assigned a project mentor and will be given the chance to work on the project With guidance and Assistance.

About our mentors

We strive to deliver the best quality training as it is one of our serious priorities, all our mentors are field professionals and have at least 8+ years of experience in the respective field.

Until when the students gets the facility of mentorship?

Students will be guided by our mentors until the end of a course. A student can seek help from our mentors even after course completion for knowledge and placement purposes.

Can a student choose to study from their desired mentor?

Every batches have respective mentors but if a student is not satisfied with any mentor’s teaching method they can raise the issue with the management and get to the facility to choose their mentor.

Project mentors

We have specified mentors for teaching and training purposes, the mentors you seek during project sessions are professionals at carrying out the project courses.

How long a student will be supported for career and job opportunities?

Students will be supported by the management in fetching job opportunities starting from the end term of the course. If any student doesn’t succeed in fetching a job they will be supported by the management for an entire 1 Year after the completion of the course.

What is the eligibility for a job assistance program?

A student will be eligible for job assistance only if they have:

  1. Minimum score of 70% in the assessment
  2. Completed the assignments and case studies
  3. Worked on and successfully completed the minimum recommended number of real-time projects

Does students get a referral for jobs?

Yes, we run Placement Assistance in where we refer eligible student profiles to different IT companies through our partnered consultancies and companies for relevant positions (Data Science/Data Analyst Roles).
For further information, you may contact the course manager/Counselor to know the eligibility of the job assistance program
Note: We don’t provide 100% Job Guarantee
SCHEDULE ONE ON ONE PROFILE REVIEW SESSION
Career Counselling,
From Domain Expert
Understand your personalised transition into data science from your current domain.
Know if your prior experience will be considered relevant for your career in data science.
Profile review will help you to resolve your queries about real time projects, job assistance, course modules etc.
Call Us +91 77956 87988 or

Data Science and AI For Managers

79,000.00

Data Science Certification Course for senior leaders, project managers to Change Your Existing Domain and start your career as data science/analytics manager.This course will benefit you to master data science skills and will help you to to handle interview with more confidence if you are looking for job in data science domain.

SKU: N/A Category:
Clear

Additional information

Select Batch

Weekday Batch: 30th September, Thu,7.30 PM To 9.30 PM, Weekend Batch : 3rd October, Sun,12.30 PM To 4 PM

#iguru_button_614953015030a .wgl_button_link { color: rgba(255,255,255,1); }#iguru_button_614953015030a .wgl_button_link:hover { color: rgba(255,255,255,1); }#iguru_button_614953015030a .wgl_button_link { border-color: transparent; background-color: rgba(255,149,98,1); }#iguru_button_614953015030a .wgl_button_link:hover { border-color: rgba(230,95,42,1); background-color: rgba(253,185,0,1); }#iguru_button_6149530156bc8 .wgl_button_link { color: rgba(241,241,241,1); }#iguru_button_6149530156bc8 .wgl_button_link:hover { color: rgba(250,249,249,1); }#iguru_button_6149530156bc8 .wgl_button_link { border-color: rgba(102,75,196,1); background-color: rgba(48,90,169,1); }#iguru_button_6149530156bc8 .wgl_button_link:hover { border-color: rgba(102,75,196,1); background-color: rgba(57,83,146,1); }#iguru_pricing_plan_61495301616e6 .pricing_title { color: #ffffff; }#iguru_pricing_plan_61495301616e6 .pricing_price_wrap .pricing_price { color: #ffffff; }#iguru_pricing_plan_61495301616e6 .pricing_cur { color: #ffffff; }#iguru_pricing_plan_61495301616e6 .pricing_desc { color: #ffffff; }#iguru_pricing_plan_61495301616e6 .pricing_desc { background-color: #333949; }#iguru_pricing_plan_61495301616e6 .pricing_content { background-color: #ffffff; }#iguru_pricing_plan_61495301616e6 .pricing_footer { background-color: #ffffff; }#iguru_button_6149530161aef .wgl_button_link { color: #ffffff; }#iguru_button_6149530161aef .wgl_button_link:hover { color: #ed3836; }#iguru_button_6149530161aef .wgl_button_link { border-color: #ed3836; background-color: #ed3836; }#iguru_button_6149530161aef .wgl_button_link:hover { border-color: #ed3836; background-color: #ffffff; }#iguru_infobox_6149530162b7e .infobox_icon { color: #00bda6; }#iguru_infobox_6149530162b7e .infobox_wrapper:hover .infobox_icon { color: #dd3333; }#iguru_infobox_6149530162b7e .infobox_icon_container { background-image: url(https://www.learnbay.co/data-science-course/wp-content/uploads/2021/02/icon_bg-01-M.png); background-position: left top; background-repeat: no-repeat; }#iguru_infobox_6149530162b7e .infobox_wrapper { padding-right: 40px !important; }#iguru_infobox_6149530162b7e .infobox_icon_container { margin-bottom: 7px !important;margin-left: -14px !important; }#iguru_infobox_614953016306d .infobox_icon { color: #00bda6; }#iguru_infobox_614953016306d .infobox_wrapper:hover .infobox_icon { color: #dd3333; }#iguru_infobox_614953016306d .infobox_icon_container { background-image: url(https://www.learnbay.co/data-science-course/wp-content/uploads/2021/02/icon_bg-02-M.png); background-position: left top; background-repeat: no-repeat; }#iguru_infobox_614953016306d .infobox_wrapper { padding-right: 40px !important; }#iguru_infobox_614953016306d .infobox_icon_container { margin-bottom: 7px !important;margin-left: -14px !important; }#iguru_infobox_61495301634e3 .infobox_icon { color: #00bda6; }#iguru_infobox_61495301634e3 .infobox_wrapper:hover .infobox_icon { color: #dd3333; }#iguru_infobox_61495301634e3 .infobox_icon_container { background-image: url(https://www.learnbay.co/data-science-course/wp-content/uploads/2021/02/icon_bg-01-M.png); background-position: left top; background-repeat: no-repeat; }#iguru_infobox_61495301634e3 .infobox_wrapper { padding-right: 40px !important; }#iguru_infobox_61495301634e3 .infobox_icon_container { margin-bottom: 7px !important;margin-left: -14px !important; }#iguru_pricing_plan_6149530164d08 .pricing_title { color: #ffffff; }#iguru_pricing_plan_6149530164d08 .pricing_price_wrap .pricing_price { color: #ffffff; }#iguru_pricing_plan_6149530164d08 .pricing_cur { color: #ffffff; }#iguru_pricing_plan_6149530164d08 .pricing_desc { color: #ffffff; }#iguru_pricing_plan_6149530164d08 .pricing_desc { background-color: #333949; }#iguru_pricing_plan_6149530164d08 .pricing_content { background-color: #ffffff; }#iguru_pricing_plan_6149530164d08 .pricing_footer { background-color: #ffffff; }#iguru_button_6149530164ff9 .wgl_button_link { color: #ffffff; }#iguru_button_6149530164ff9 .wgl_button_link:hover { color: #ed3836; }#iguru_button_6149530164ff9 .wgl_button_link { border-color: #ed3836; background-color: #ed3836; }#iguru_button_6149530164ff9 .wgl_button_link:hover { border-color: #ed3836; background-color: #ffffff; }#iguru_infobox_6149530165dfc .infobox_icon { color: #00bda6; }#iguru_infobox_6149530165dfc .infobox_wrapper:hover .infobox_icon { color: #dd3333; }#iguru_infobox_6149530165dfc .infobox_icon_container { background-image: url(https://www.learnbay.co/data-science-course/wp-content/uploads/2019/09/icon_bg-01.png); background-position: left top; background-repeat: no-repeat; }#iguru_infobox_6149530165dfc .infobox_wrapper { padding-right: 40px !important; }#iguru_infobox_6149530165dfc .infobox_icon_container { margin-bottom: 7px !important;margin-left: -14px !important; }#iguru_infobox_6149530166283 .infobox_icon { color: #00bda6; }#iguru_infobox_6149530166283 .infobox_wrapper:hover .infobox_icon { color: #dd3333; }#iguru_infobox_6149530166283 .infobox_icon_container { background-image: url(https://www.learnbay.co/data-science-course/wp-content/uploads/2019/09/icon_bg-02.png); background-position: left top; background-repeat: no-repeat; }#iguru_infobox_6149530166283 .infobox_wrapper { padding-right: 40px !important; }#iguru_infobox_6149530166283 .infobox_icon_container { margin-bottom: 7px !important;margin-left: -14px !important; }#iguru_infobox_61495301666be .infobox_icon { color: #00bda6; }#iguru_infobox_61495301666be .infobox_wrapper:hover .infobox_icon { color: #dd3333; }#iguru_infobox_61495301666be .infobox_icon_container { background-image: url(https://www.learnbay.co/data-science-course/wp-content/uploads/2019/09/icon_bg-02.png); background-position: left top; background-repeat: no-repeat; }#iguru_infobox_61495301666be .infobox_wrapper { padding-right: 40px !important; }#iguru_infobox_61495301666be .infobox_icon_container { margin-bottom: 7px !important;margin-left: -14px !important; }@media only screen and (max-width: 767px){ #iguru_spacer_6149530166bc0 .spacing_size{ display: none; } #iguru_spacer_6149530166bc0 .spacing_size-mobile{ display: block; } }@media only screen and (max-width: 767px){ #iguru_spacer_6149530168fc6 .spacing_size{ display: none; } #iguru_spacer_6149530168fc6 .spacing_size-mobile{ display: block; } }@media only screen and (max-width: 1200px){ #iguru_spacer_6149530170c79 .spacing_size{ display: none; } #iguru_spacer_6149530170c79 .spacing_size-desktops{ display: block; } }#iguru_button_6149530170dcd .wgl_button_link { border-width: 2px; }#iguru_button_6149530170dcd .wgl_button_link { color: #1e73be; }#iguru_button_6149530170dcd .wgl_button_link:hover { color: #2c2c2c; }#iguru_button_6149530170dcd .wgl_button_link { border-color: #2641ef; background-color: #ffffff; }#iguru_button_6149530170dcd .wgl_button_link:hover { border-color: #ff6d34; background-color: #ffffff; }#iguru_button_6149530170dcd a { box-shadow: 0px 10px 10px 0 rgba(255,255,255,0.4) }#iguru_button_6149530170dcd a:hover { box-shadow: 0px 10px 10px 0 rgba(255,255,255,0.4) }@media only screen and (max-width: 767px){ #iguru_spacer_614953017115e .spacing_size{ display: none; } #iguru_spacer_614953017115e .spacing_size-mobile{ display: block; } }#iguru_button_61495301771bc .wgl_button_link { border-width: 2px; }#iguru_button_61495301771bc .wgl_button_link { color: #ffffff; }#iguru_button_61495301771bc .wgl_button_link:hover { color: #2c2c2c; }#iguru_button_61495301771bc .wgl_button_link { border-color: #ff6d34; background-color: #ff6d34; }#iguru_button_61495301771bc .wgl_button_link:hover { border-color: #ff6d34; background-color: #ffffff; }#iguru_button_614953017c5e4 .wgl_button_link { border-width: 2px; }#iguru_button_614953017c5e4 .wgl_button_link { color: #ffffff; }#iguru_button_614953017c5e4 .wgl_button_link:hover { color: #2c2c2c; }#iguru_button_614953017c5e4 .wgl_button_link { border-color: #ff6d34; background-color: #ff6d34; }#iguru_button_614953017c5e4 .wgl_button_link:hover { border-color: #ff6d34; background-color: #ffffff; }@media only screen and (max-width: 992px){ #iguru_spacer_61495301852ff .spacing_size{ display: none; } #iguru_spacer_61495301852ff .spacing_size-desktops{ display: block; } }@media only screen and (max-width: 991px){ #iguru_spacer_61495301852ff .spacing_size{ display: none; } #iguru_spacer_61495301852ff .spacing_size-tablet{ display: block; } }@media only screen and (max-width: 480px){ #iguru_spacer_61495301852ff .spacing_size{ display: none; } #iguru_spacer_61495301852ff .spacing_size-mobile{ display: block; } }#time_line_614953018659f .time_line-date{ color: #3aa0e8; }#time_line_614953018659f .time_line-check{ border-color: #3aa0e8; background: #3aa0e8; }#time_line_614953018659f .time_line-content:before, #time_line_614953018659f.item_active .time_line-check{ background: #3aa0e8; }#time_line_61495301865cb .time_line-date{ color: #3aa0e8; }#time_line_61495301865cb .time_line-check{ border-color: #3aa0e8; background: #3aa0e8; }#time_line_61495301865cb .time_line-content:before, #time_line_61495301865cb.item_active .time_line-check{ background: #3aa0e8; }#time_line_61495301865e1 .time_line-date{ color: #3aa0e8; }#time_line_61495301865e1 .time_line-check{ border-color: #3aa0e8; background: #3aa0e8; }#time_line_61495301865e1 .time_line-content:before, #time_line_61495301865e1.item_active .time_line-check{ background: #3aa0e8; }#time_line_61495301865f2 .time_line-date{ color: #3aa0e8; }#time_line_61495301865f2 .time_line-check{ border-color: #3aa0e8; background: #3aa0e8; }#time_line_61495301865f2 .time_line-content:before, #time_line_61495301865f2.item_active .time_line-check{ background: #3aa0e8; }@media only screen and (max-width: 1200px){ #iguru_spacer_6149530186a69 .spacing_size{ display: none; } #iguru_spacer_6149530186a69 .spacing_size-desktops{ display: block; } }#iguru_button_6149530186ba4 .wgl_button_link { border-width: 2px; }#iguru_button_6149530186ba4 .wgl_button_link { color: #ffffff; }#iguru_button_6149530186ba4 .wgl_button_link:hover { color: #2c2c2c; }#iguru_button_6149530186ba4 .wgl_button_link { border-color: #ff6d34; background-color: #ff6d34; }#iguru_button_6149530186ba4 .wgl_button_link:hover { border-color: #ff6d34; background-color: #ffffff; }@media only screen and (max-width: 1200px){ #iguru_spacer_614953018822c .spacing_size{ display: none; } #iguru_spacer_614953018822c .spacing_size-desktops{ display: block; } }#iguru_button_614953018836e .wgl_button_link { border-width: 2px; }#iguru_button_614953018836e .wgl_button_link { color: #ffffff; }#iguru_button_614953018836e .wgl_button_link:hover { color: #2c2c2c; }#iguru_button_614953018836e .wgl_button_link { border-color: #ff6d34; background-color: #ff6d34; }#iguru_button_614953018836e .wgl_button_link:hover { border-color: #ff6d34; background-color: #ffffff; }@media only screen and (max-width: 1200px){ #iguru_spacer_6149530189861 .spacing_size{ display: none; } #iguru_spacer_6149530189861 .spacing_size-desktops{ display: block; } }#iguru_img_layer_614953018b42c .img_layer_image_wrapper:nth-child(1) .img_layer_image {transition: all 800ms; -webkit-transition-delay: 0ms; -moz-transition-delay: 0ms; -o-transition-delay: 0ms; transition-delay: 0ms;}#iguru_img_layer_614953018b42c .img_layer_image_wrapper:nth-child(2) .img_layer_image {transition: all 800ms; -webkit-transition-delay: 600ms; -moz-transition-delay: 600ms; -o-transition-delay: 600ms; transition-delay: 600ms;}#iguru_img_layer_614953018b42c .img_layer_image_wrapper:nth-child(3) .img_layer_image {transition: all 800ms; -webkit-transition-delay: 1200ms; -moz-transition-delay: 1200ms; -o-transition-delay: 1200ms; transition-delay: 1200ms;}#iguru_img_layer_614953018b42c .img_layer_image_wrapper:nth-child(4) .img_layer_image {transition: all 800ms; -webkit-transition-delay: 1800ms; -moz-transition-delay: 1800ms; -o-transition-delay: 1800ms; transition-delay: 1800ms;}#iguru_button_614953018be0f .wgl_button_link { color: #ffffff; }#iguru_button_614953018be0f .wgl_button_link:hover { color: #000000; }#iguru_button_614953018be0f .wgl_button_link { border-color: #ff6d34; background-color: #ff6d34; }#iguru_button_614953018be0f .wgl_button_link:hover { border-color: #ff6d34; background-color: #ffffff; }#iguru_soc_icon_wrap_614953019549f a{ background: transparent; }#iguru_soc_icon_wrap_614953019549f a:hover{ background: transparent; border-color: #3aa0e8; }#iguru_soc_icon_wrap_614953019549f a{ color: #acacae; }#iguru_soc_icon_wrap_614953019549f a:hover{ color: #ffffff; }#iguru_soc_icon_wrap_614953019549f { display: inline-block; }.iguru_module_social #soc_icon_61495301954d01{ color: #ffffff; }.iguru_module_social #soc_icon_61495301954d01:hover{ color: #ffffff; }.iguru_module_social #soc_icon_61495301954d01{ background: #44b1e4; }.iguru_module_social #soc_icon_61495301954d01:hover{ background: #44b1e4; }
Get The Learnbay Advantage For Your Career
Note : Our programs are suitable for working professionals(any domain). Fresh graduates are not eligible.
Overlay Image
GET THE LEARNBAY ADVANTAGE FOR YOUR CAREER
Note : Our programs are suitable for working professionals(any domain). Fresh graduates are not eligible.