Most of the industry sectors today are coping with vast amounts of data for which they need reliable management and storage facilities. Since, the amount of data is constantly increasing the requirement for Data Science experts.
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Combo Course
Why to choose us?
Free live demo
1 hr free live interaction class are available, one on one session to clarify all your doubts.
Individual attention
Batch size max 4 – 5 so that trainer can easily concentrate on all
Trainer profile
Certified trainers having 8 years of work experience in IT domain, with relevant field
Certificate
Course completion certificate will provide at the end of the course.
About the course
What is Data Science?
Data science is a multidisciplinary blend which uses different method, algorithms, and systems to extract facts and insights from the business data which is at various forms like structured and unstructured. Using Python Data Analysis Library Pandas, the whole thing can be taken care from importing data from Excel till processing sets for time-series analysis.
We modify our Data Science Course to suit each and every student in a unique way. Our Data Science Training Program includes all the main topics such as data mining, data analytics, deep learning with Python, data science with Python, Predictive Analytics and lot more. We can directly hit Data Science Algorithms if you are already high-quality at Python Programming. To make you skillful in Python, we also give Python Classroom Course, Python Online Course and Python tutorial for beginners.
Best Data Science with Python Training in Bangalore
Get Industry Recognized Certifications & Jobs in Top MNC’s
Our certifications will help you get sited easily in top companies such as IBM, HCL, Cognizant, CTS, Dell, TCS, Accenture, etc. Since our certifications are standard globally, you will get the job with the right salary package soon after completing the course training. Following are the payback you’ll from our certification :
- It is a broadly accepted certification, especially when it comes to top companies
- As a fresher, it will increase your portfolio and resume
- It gives them skills to clear an evaluation effectively
- Improves your efficiency for problem-solving in interview
- It develops your knowledge in completing projects in your current company
- Boost the repute of your careers
- Build Sound decision-making capability to get successful in jobs
- Enhances knowledge and expertise and trains you for further tasks
- It is used as digital proof of effectiveness
- It enhances an individual’s self and reliability
- Improves work prospects, rises in income, portability of jobs.
Trainer Profile of Data Science Python Training in Bangalore
Our Trainers provide complete liberty to the students, to explore the subject knowledge and learn based on real-time examples. Our trainers helps the candidates in completing their projects and even prepare them for interview preparation questions and answers. Candidates are feel free to ask any questions at any point in time.
- More than 7+ Years of familiarity in the domain.
- Trained more than 3000+ students in a year.
- Strong Theoretical & Practical Knowledge both.
- Certified Professionals with High Grade in the market.
- Well connected with recruiting HRs in multinational companies.
- Expert level Subject facts and fully up-to-date on real-world industry applications.
- Trainers have knowledgeable on multiple real-time projects in their Industries.
Our Trainers are working in multinational company such as CTS, TCS, HCL Technologies, ZOHO, Birlasoft, IBM, Microsoft, HP, Scope, Philips Technologies etc .
Job Responsibilities
Data Science Python training in Marathahalli
Data Science Python training in Kalyan Nagar
Quick Enquiry
Data Science Course Syllabus
• History of Python
• Introduction
• Starting with Python
• Execute python script
• Indentation
• Data Types and Variables
• Operators
• Lists and Strings
• List Manipulations
• Shallow and Deep Copy
• Dictionaries
• Set and Frozen sets
• Tuple
• Input from keyboard
• If-else Block
• Loops, While Loop
• For Loop
• Iterators and Iterables
• Output with Print
• String Modulo
• Format Method
• Introduction to Functions
• Recursion and Recursive Functions
• Parameter Passing in Functions
• Namespaces
• Global and Local Variables
• Decorators
• Read and Write Files
• Modules
• Packages
• Regular Expressions
• Lambda, Filter & Map Operators
• List Comprehension
• Iterators and Generators
• Exception Handling
• Tests, DocTests & UnitTests
• Introduction
• Class and Instance Attributes
• Properties v/s getters and setters
• Inheritance
• Abstract Classes
• Multithreading
• Memory Management
• Logging Facility
• Argument Parser
• Invoking Sub process
• Lincache, fnmatch etc
Module 2 - Sql Syllabus
MYSQL Server Basics
Database models
ER Model Overview
Data types
Understanding Test Database
Basics Queries
Removing Duplicates
Data Filters Using Operators
Data Sorting
Grouping
Joints
Arithmetic and String functions
Advanced Functions
SET Operators
Creating Complex Queries
DML operations – Insert, Update & Delete
TSQL
Database Objects – Create, Alter and Drop Tables
Views
Complex Views
Indexes
Advanced Indexes Concepts
How Data is Stored
Security – User Management
Cursors
Nested Cursors
Functions
Procedures
Interoperability between Functions & Procedures
Module 3 - Data science with Python syllabus
• Data Types
• Strings in Python
• Variables and values
• Boolean Types
• Loops and decision Making
• Functions
• Data Types
• Strings in Python
• Variables and values
• Boolean Types
• Loops and decision Making
• Functions
• Getting datas from internet
• JSON
• XML
• Google API
• Beautiful soap
• Log in to web server
• Basics
• Normalizations
• SQL Integration with Python
• Working across multiple Tables
• Numpy Intros
• Numpy with Analytics
• Pandas Data Reader
• Google Finance Data
• Time Series Analysis
• Data Cleaning
• Data Visualization
• Sentiment Analysis
• Words Cloud
• Text analysis
• Topics on Modelling
• Introduction to Network Analysis
• Construct a simple Network
• Graph Drawing
• Network Analysis Algorithm
• Classifications of algorithm
• Regressions
• Assignments
• K NN Algorithm
• Construct a simple Network
• Clustering
• Assignments
Module 4 - Tableau Course Syllabus
Introduction to Tableau and an overview of the different versions
Installing Tableau Desktop
Tableau Help and online resources
Understanding Tableau User Interface
Exploring Tableau File Types
Understanding Green and Blue Pills
Working with Available Data Sources
Working with extracts instead of live connections
Working with Excel Data Interpreter
Understanding Metadata and sharing data source connections
Filtering data from your d
Learning how to Split the fields
Pivoting Data
The Show Me Feature
Crosstabs and Heat Maps
Using Bar, Stacked Bar and Side-by-side Bars
Pie Charts
Line and Area Charts
Working with Packed Bubble
Using Tree maps
Creating a Basic Scatter Plot
Creating a Basic Maps
Introduction to Calculations (this will explain the various flavours of calculations and the
mechanics of calculations)
Understanding Basics calculations
Understanding String Calculations
Learning about Boolean, If-Then calculations, and Case statements
Understanding the Basics of Date Calculations
Understanding Aggregation and Disaggregation
Using calculations to add insight to your visualizations
Introduction to Mapping in Tableau
Create a standard map view
Dealing with map errors
Customizing a standard map view
Using filters in maps
Quiz
Introduction to Dashboards
Understanding Dashboard Actions
Understanding Dashboard formatting basics
Understanding Workbook level formatting (i.e. font styling, titles, lines)
Assembling Your Dashboards Into A Story
Focusing on the narrative
Using colour with a purpose
Understanding the importance of using tooltips for your audience
Using a Parameter To Focus the Audience’s Attention
Removing clutter in your Dashboard
How to export your dashboard to another file type
Module 5 - Power BI Course Syllabus
Get Started with Power BI
Overview: Power BI concepts
Sign up for Power BI
Overview: Power BI data sources
Connect to a SaaS solution
Upload a local CSV file
Connect to Excel data that can be
refreshed
Connect to a sample
Create a Report with Visualizations
Explore the Power BI portal
Overview: Visualizations
Using visualizations
Create a new report
Create and arrange visualizations
Format visualization
Create chart visualizations
Use text, map, and gauge
visualizations and save a report
Use a slicer to filter visualizations
Sort, copy, and paste visualizations
Download and use a custom visual
Modify and Print a Reports
Rename and delete report pages
Add a filter to a page or report
Set visualization interactions
Print a report page
Send a report to PowerPoint
Create a Dashboard
Create and manage dashboards
Pin a report tile to a dashboard
Pin a live report page to a dashboard
Pin a tile from another dashboard
Pin an Excel element to a dashboard
Manage pinned elements in Excel
Add a tile to a dashboards
Build a dashboard with Quick Insights
Set a Featured (default) dashboard
Tweak your dataset for Q&A
Enable Cortana for Power BI
Share Data with Colleagues and
Others
Publish a report to the webs
Manage published reports
Share a dashboard
Create an app workspace and add
users
Use an app workspace
Publish an app
Create a QR code to share a tile
Embed a report in SharePoint Online
Use Power BI Mobile Apps
Get Power BI for mobile
View reports and dashboards in the app
Use workspaces in the mobile app
Sharing from Power BI Mobil
Use Power BI Desktop
Install and launch Power BI Desktop
Get data
Reduce data
Transform data
Relate tables
Get Power BI Desktop data with the
Power BI service
Export a report from Power BI service to Desktop
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Feb 7th | Mon-Fri (45 Days) | FILLING FAST 7AM -11AM, 4PM – 9.30PM. |
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Feb 15th | Mon-Fri (45 Days) | FILLING FAST 7AM -11AM, 4PM – 9.30PM |
Feb 21th | Mon-Fri (45 Days) | FILLING FAST 7AM -11AM, 4PM – 9.30PM |
Feb 28th | Mon-Fri (45 Days) | FILLING FAST 7AM -11AM, 4PM – 9.30PM |
Talk to Us
For Online and Classroom Training
+91 9514203013
FAQ
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- Encapsulation
- Polymorphism
- Abstraction
- Interface
Learn More Technologies gives many suitable modes of training to the students like
- Classroom Training
- Live Instructor Online Training
- Customized Training
- One-One Training.