Additional information
Select Batch | Weekend Batch : 15th May, 12:30 PM To 4 PM ( 25 Seats Left), Weekday Batch : 12th May, 8 PM To 10:00 PM ( 20 Seats Left) |
---|
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 and its Challenges?
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 a 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
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 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
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 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
Project : Loan Default Prediction
Domain – Banking & Finance
DataSet: Banking Data
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 : Clustering Customers
Domain – Retail industry
DataSet: BigBazar/Future Group
Big Bazaar has retail outlets across major metropolitan cities in India. With the help of machine learning algorithms, we can better understand customer behaviour and understand their buying needs better.BigBazaar runs various loyalty
programs, festive offers which provide their customer more opportunities to
avail discounts.
Project : IBM HR Analytics
Domain – Demand/Supply
DataSet: IBM
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 : Forecasting Uber Demand
Domain – Demand/Supply
DataSet : Uber & Rapido
The goal is to create an interactive dashboard using Tableau This Tableau Dashboard can be used to get historical insights into a neighbourhood, For example, see its upcoming forecasted demand, increase the accuracy, decrease surge pricing events.
Project : Analyzing Health Data and tracking human activity
Domain – Healthcare
DataSet: Samsung
The goal is to breakdown all the data that the Samsung Health
the app has collected and seen what useful insights we can gain by analyzing it.
Project : Identify fraudulent credit card transactions.
Domain – Banking & Finance
DataSet : Banking Dataset
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
Domain – E-Commerce
DataSet : Amazon Data
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
Domain – Travel & Hospitality
DataSet: Airbnb
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
Domain – Media and Entertainment
DataSet :Netflix
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 finding interesting insights.
Project : Walmart Sales Forecasting
Domain – Retail
DataSet : Walmart
This dataset contains the sales for each department from Walmart
a 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
Domain – Automation
DataSet :BMW dataset
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
Domain – Manufacturing
DataSet :Bosch
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: -Smart Supply Chain for Big Data Analysis
Domain – Supply Chain
DataSet :Dataco
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.
Project : -Trending YouTube Video Statistics
Domain – Social Media
DataSet: youtube
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 Categorising YouTube videos based on their comments and statistics
Training ML algorithms like RNNs to generate their own YouTube comments.
Project : -Identify And Predict Customer churn in telecom industry
Domain – Telecom
DataSet :Telecom
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 the customer churn in the telecom industry.
Surely, a wide range of subjects can be learned in the Data Science and AI Certification courses. Indeed, the five stages of the Data science lifecycle are covered. Certainly, graduates from any field can enroll in the domain specialisation course.
During our Data Science and AI Certification course we teach:
Indeed, data science is used to measure success and plan future goals. Surely, it involves gathering and analysing data from relevant sources. As a result, companies nowadays rely on data science.
As a matter of fact, data scientists use their knowledge to detect trends and deal with data. At the same time, they find solutions to problems using expertise and a belief that the ideas may be incorrect.
Data scientists are hired for jobs such as:
Currently, data science jobs are in high demand in Bangalore and across many industries.
Indeed, the Data Science course is open to anyone with 1+ year of experience. As a matter of fact, there is a different course for Programmers and Core tech background professionals.
Undoubtedly, Fresh graduates from any stream can seek the Data Science course. At the same time, any college-going student can enroll in weekend classes as well.
Additionally, we offer flexibility for choosing customized courses and data science professional mentors. Indeed, we are committed to producing top-quality data science professionals for the upcoming years.
So, let’s look at the reasons that tell you why it is beneficial.
Undoubtedly, Learnbay is recognized as the finest Data Science Training Institute in Bangalore. In fact, the program offers Data Science Certification in collaboration with IBM.
However, obtaining Data science certification online training in Bangalore is simple. Additionally, get certified in data science in Bangalore by getting good scores in assessments. Additionally, qualify the Job help eligibility and get exciting job offers in Bangalore and all over India.
Indeed, data Science Training prepares students for the growing demand. Additionally, it gives experts data management tools. The following are the advantages of choosing a data science course:
Yes indeed, the data science course in Bangalore offered by Learnbay data science institute is suitable for freshers, college-going students, managers, and working professionals. Undoubtedly, at Learnbay, we provide foundation courses and fresher programs. Surely, we offer a range of specialized courses for different groups of learners. You can visit our website for course descriptions and data science projects for each program in detail.
However, the data science course training fees in Bangalore depends on the program or course you choose to study. Nevertheless, it should be noted that the fees for different data science courses are mentioned below:
Indeed, Learnbay data science Institute provides data science training in Bangalore with job help. Additionally, we help data science enthusiasts to get through job interviews and resume preparation. Surely, Our strong ties with corporates and the IT industry helps in bulk placements. Moreover, we ensure to support candidates after the course completion. Surely, career counselling and interview preparation are our primary concerns for every candidate. At the same time, Getting hired depends on passing mock interviews and regular assessments.
Indeed, Learnbay is an ideal data science course training Institute in Bangalore. We are one of the best data science learning institutes in urban cities such as Bangalore. However, the primary focus of Learnbay is to:
As a matter of fact, IBM and Learnbay have joined to offer a data science course in Bangalore and other cities over India. Surely, IBM and Learnbay work together to fulfil the following goals:
Surely, Artificial intelligence allows machines to behave and think like humans. Indeed, Machine learning is a branch of artificial intelligence based on a vast amount of data. Certainly, it is used in different artificial intelligence approaches.
As a result, Artificial Intelligence and Machine Learning courses in Bangalore are getting popular. Again, Learnbay data science certifications in Bangalore teaches Artificial Intelligence and Machine Learning. Not to mention, Learnbay Data Science Institute offers customised data science courses based on candidate needs.
The data science course by Learnbay is conducted through both online mode and classroom mode. Moreover, the live data science course online classes are accessible to our online learners. However, the full-time or classroom mode classes are accessible in our institute premises on the 2nd Floor, Classic Aura, Service Rd, above Hyderabadi biryani house, Kadubeesanahalli, Bengaluru Karnataka.
The duration of this data science training in Bangalore depends on the course chosen in the first place. However, the maximum period of a data science course is six months to 12 months. Moreover, It includes live lectures and hands-on practical training on industrial projects. The classes are accessible even after a year of course completion.
Yes indeed, you can pursue a data science course in Bangalore after graduation. At the same time, depending on your needs, you can select the foundation or beginners’ curriculum. We also have a unique course in data science for professionals.
Learnbay is the best data science institute in Bangalore since it is best suited for:
Indeed, Learnbay is recognised as the finest Data Science Training Institute in Bangalore. However, you can attend the classroom training if you live close to the lecture halls in Bangalore. In contrast, the sessions will also be conducted Live-Online.
Indeed, the eligibility for the data science course in Bangalore are:
Surely, the programming languages taught in the data science course in Bangalore are Python and R, MySQL, and others. Special attention is paid to these two languages due to the high demand for model training.
Indeed, Bangalore is a hub for high-tech and service industries. As a result, there are several opportunities for a data scientist in Bangalore, India’s “Silicon Valley.”
Indeed, the essential features of the Learnbay data science course in Bangalore are:
Firstly, enroll in Learnbay’s data science course in Bangalore to start a career in data science. Indeed, this course will help you master data science abilities. Additionally, it also helps you prepare for interviews if you want to work in the data science field.
How to Find Data Science and Business Analytics in Bangalore?
Surely, this Data Science certification training provides hands-on experience with essential technologies. Such as R, Python, Machine Learning, etc through live interaction and industry projects. Kindly visit Learnbay and enroll in the course immediately.
Should I get a data science certification? Surely, it’s the most perplexing question that every aspiring data scientist must confront. Additionally, there are a few queries like – Will it boosts the weight of my resume, or will it assist me in landing a job? As a result, there is increased stress and confusion.
A data science certification undoubtedly has some advantages. Without a doubt, it demonstrates your love and passion for data science. Still, there is a caution — due to the surge in data science, many courses have become widespread or general.
To stand out, enroll in a course that exposes you to professionals and projects. Indeed, Certification is used as a yardstick for measuring exceptional talent.
As our courses include an IBM data science certification, they help you take it further.
We pride ourselves on being the best institute for a data science course in Bangalore. Additionally, we include a non-technical domain course that begins with the basics.
Firstly, after payment, you will get an email confirming your enrollment. It will outline how to get the Data Science course materials. By following the steps, you may go through the video lessons.
Indeed, the following are the top data science certification courses provided:
According to Payscale, a data scientist’s salary in different metropolitan cities of India are as follows:
City | Pay Scale |
---|---|
Mumbai | Rs.788,789 per annum |
Chennai | Rs.794,403 per annum |
Bangalore | Rs.984,488 per annum |
Hyderabad | Rs.795,023 per annum |
Pune | Rs.725,146 per annum |
Kolkata | Rs. 402,978 per annum |
It is self-evident that Bangalore offers a higher income and more excellent prospects for the growth of a data scientist. Learnbay’s data science course will equip you to apply for any data science job across India or anywhere else in the world.
Throughout the world the wages for data science jobs varies as follows:
City | Pay Scale |
---|---|
United States | $96,00,000 USD per annum |
United Kingdom | £40,431 per annum |
Canada | $79,00,000 USD per annum |
Australia | $91,857 AU per annum |
Singapore | S$71,011 per annum |
New Zealand | Nz $73,869 per annum |
South Africa | R405594 per annum |
The following books are obligatory reading materials for any data science professionals:
Flexible Two-Year Subscription
Contact us via the form on the right side of any Learnbay page, the Live Chat link, or contacting Help & Support.
Indeed, businesses embrace digital transformation, making a profession in data science attractive. As a result, companies are becoming more digital, and data scientists will remain in demand. Consequently, extensive use of business analytics has been observed in the past few years. Certainly, Business analytics plays a crucial role in surplus growth and profits. As a result of the present skills scarcity, firms are willing to pay higher compensation. Indeed, you can qualify for this rewarding job with Learnbay’s Data Science course.
Indeed, data science is a broad field, and it is impossible to become an expert in it in six months or a year. However, having a basic understanding of programming and analytics tools is required. Nevertheless, using Data Science skills is simple after this Data Science course in Bangalore.
Will a Data Science course in Bangalore land me a good career?
Obviously, businesses are embracing digital transformation. As a result, the increased reliance on data makes a career in data science quite lucrative. Evidently, the businesses are ramping up their digital activities. Therefore, data science abilities will continue to be in high demand in the foreseeable future. In addition, the extensive use of Data Science has been observed in the past few years. Of course, data science plays a key role in surplus growth and profits. Additionally, given the current skills shortage, businesses are willing to offer data scientists greater wages for the data scientist, Data Science, machine learning, and Artificial Intelligence roles. Undoubtedly, you can qualify for this rewarding job with Learnbay’s Data Science course in Hyderabad.
Due to the rising need for data scientists, companies are willing to pay higher rates. However, one must show their data science expertise and get industrial exposure. Indeed, Learnbay’s Data Science certification teaches new graduates all essential data science skills. Additionally, it prepares them for the workforce by requiring them to work on real-world projects.
Indeed, the Data Science training in Bangalore covers advanced machine learning and AI. Certainly, Learnbay has created various Artificial Intelligence methods. Indeed, our Data Scientists in Bangalore have developed the following core competencies:
Indeed, our Data Scientists are skilled in Python, C++, Java, etc. Certainly, Data Science demands good coding skills. So does our curriculum.
Data preparation and storage capacity is another helpful data science skill. So, we need a data scientist who can build, extract, transform, and store data pipelines. Additionally, Learnbay’s industrial projects aid in data engineering skills mastery.
Indeed, the important data science skill is data analysis. Although, data collection takes time, finding valuable patterns takes even longer. Data visualisation in the form of histograms, box plots, heat maps, etc., is also required. However, only a data fanatic with data analytics abilities can do all this. Nevertheless, Learnbay’s data science curriculum includes data visualisation training. So, develop Business Analytics abilities to specialise.
Indeed, a data scientist’s main responsibility is to create data analytics models. Thus, this course will teach you how to use machine learning and AI approaches. Additionally, the programs help them find connections between data sets. However, model development requires extensive testing.
After creating a machine learning model, they must be evaluated for implementation. When installing a machine learning model, various factors must be considered. Thus, the performance parameter is based on flexibility.
Indeed, data science education often includes software security. Thus, training is required to secure machine learning models. Indeed, Learnbay’s data science courses teach all these skills for a low data science course fee.
Indeed, Learnbay provides job help and practise interviews for budding Data Scientists in Bangalore. Additionally, we aid with resume writing, interview prep, and job profile selections. Besides, our firm bond with MNCs and IT companies comes in handy during bulk placements. So, all you need to do is sit back, take classes, relax and let us do our job!
Indeed, the Data Science course has no requirements as all courses are taught from the beginning. But, if you are from a non-technical and non-programming background. In that case, We provide special classes and help to learn to program.
In case you miss classes, Learnbay will provide you with backup classes in other batches. But, if you miss more classes, you can request a batch change and join our next batch. To solve this issue, we provide a Flexi-pass option for our data science course.
Additionally, those who enroll for live classroom training are eligible for a Flexi-pass of 6 months. This allows you to join live classroom sessions from any batch for six months and learn at your own pace. This option also helps you to finish the course early as you can attend many batches.
This option is best for someone working in shifts or who needs to work on weekends sometimes.
The total duration of Data Science 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.
Resume Preparation Session: Expert guidance for writing a resume for data scientist Role
Preparing Project For interviews: This 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
Note: We don’t provide any 100% Job Guarantee.
Note: We don’t provide a 100% Job Guarantee
The data science course fee is different for different programs. There is 0% EMI Available on Major credit cards. Please check with our sales team to know how 0% EMI on credit cards works.
Data science course cost in Bangalore is much lower with 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.
Group Discount: Group discount is applicable if you are joining with your friends.
Click here to download the list of projects
We have specified mentors for teaching and training purposes, the mentors you seek during project sessions are data science professionals at carrying out the project courses.
₹65,000.00
IBM certified Data Science Course For Working Professional to Change Your Existing Domain and start your career in data science.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.
Select Batch | Weekend Batch : 15th May, 12:30 PM To 4 PM ( 25 Seats Left), Weekday Batch : 12th May, 8 PM To 10:00 PM ( 20 Seats Left) |
---|
Data Science Certification Training locations in Bangalore : Ammrutha halli [560092], Maruthi Seva Nagar [560033], Kuvempu Layout [560077], Bellandur [560103], Jayanagar III Block [560011], Anandnagar [560024], Nandinilayout [560096], B SK II Stage [560070], Indiranagar [560038], Yelahanka [560063], Chickpet [560053], Domlur [560071], Bansashankari III Stage [560085], Vimanapura [560017], Nagarbhavi [560072], Basaveshwaranagar [560079], Bommanahalli [560068], Mico Layout [560076], Electronic City [560100], Taverekere [560029], Nehru Nagar [560020], Agram[560007], Halsuru Pete [560002], Basavanagudi [560004], R.M.V. Extension II [560094], Jayanagar [560041], Carmelaram [560035], New Thippasandra [560075], Kanakanagar [560032], Nayandahalli [560039], Fraser Town [560005], Jalahalli East [560014], Kacharakanahalli [560084], Malleswaram West [560055], Bannerghatta [560083], Srirampuram [560021], Rajarajeshwarinagar [560098], Sivan Chetty Gardens [560042], Dommasandra [562125], Whitefield [560066], Vidyaranyapura [560097], Bolare [560082], Mathikere [560054], Doddanekkundi [560037], Hampinnagar [560104], C.V.Raman Nagar [560093], Chikkabanavara [560090], Attur [560064], Kumbalagodu [560074], Bhattarahalli [560049], Chikkalasandra [560061], Sharada Nagar [560065], Jalahalli West [560015], H.K.P Road [560051], Jp Nagar III Phase [560078], Sadashiva nagar [560080], Krishnarajapuram R S [560016], Mahalakshipuram Layout [560086], Guddadahalli [560026], Chudenapura [560060], Vidhana Soudha [560001], Shanthinagar [560027], Rajaji Nagar [560010], Chandapura [560099], Ramakrishna Hegde Nagar [560045], Shalabh Bhatnagar [560012], Peenya [560058], Ashoknagar [560050], Jalahalli Nacen [560013], Banawadi [560043], Malleswaram [560003], Doddakallasandra [560062], K.G Road [560009], Muthusandra [560087], Marathahalli [560056], JC Nagar [560006], Chamrajpet [560018], HSR Layout [560102], Devanagundi [560067], Yeswanthpura [560022], Mahadevapura [560048],Hulsur Bazaar [560008],Magadi Road [560023], Adugodi [560030], Bagalgunte [560073], Devasandra [560036], Rv Niketan [560059], Narasimharaja Colony [560019], Koramangala VI Bk [560095], Agara [560034], Vijayanagar East [560040], Benson Town [560046], Viveknagar S.O [560047], Dasarahalli [560057], Bapagrama [560091], Richmond Town [560025].
Locations Offered : Data Science Training in Bangalore, Data Science Course in Bangalore, Data Science Training in BTM, Data Science Training in Marathahalli, Data Science Institute in Bangalore, Data Science Training in Whitefield, Data Science Training in Kundalahalli, Data Science Training in ITPL, Data Science Training Institute in Marathahalli, Data Science Course in BTM, Data Science Course in Marathahalli, Data Science Course in Whitefield, Data Science Course Bommanahalli, Data Science Training in Bommanahalli, Data Science Training in Electronic city, Data Science Training in Koramangala, Data Science Classes in BTM, Data Science Classes in Bommanahalli, Data Science Classes in Whitefield, Data Science Classes in Marathahalli, Data Science Course in Koramangala, Data Science Training in Jayanagar, Data Science Certification in Bangalore, Data Science Certification Training in Bangalore, Data Science Certification in BTM, Data Science Certification in Whitefield, Best Data Science Training, Best Data Science Course