Complete Data Science Online Course for Freshers & Working Professionals, Covering Python, Advanced Statistics in Python, Machine & Deep Learning
4.2/5
4.8/5
4.6/5
4.3/5
4.5/5Course Duration
160 Hrs.Live Project
14 ProjectCertification Pass
GuaranteedTraining Format
Live Online /Self-Paced/ClassroomWatch Live Classes
Speciality
200+
Professionals Trained
3+
Batches every month
20+
Countries & Counting
100+
Corporate Served- Taking online Data Science Training in India in 2025 opens up opportunities in a data-driven world. As technology grows, Data Science and Machine Learning have become essential skills for anyone looking to work in tech or business. Data Science Training in India has become highly popular in 2025, offering students the opportunity to learn essential skills for the data-driven job market.
Data Science Online Course
- In-Demand Skills: Learning Data Science and Machine Learning is key to landing well-paying jobs in today's job market. If youre looking for a course with job support, you can consider enrolling in a Data Science Course Online with Placement, ensuring you get the help you need to land a job.
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- Best Online Data Science Courses in 2025
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- Data Science Management Course Description:
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Data Science Fundamentals: Understand the key principles and methods used to analyze and interpret complex data sets.
Machine Learning Techniques: Learn how to implement various machine learning algorithms for predictive analytics and data-driven decision-making.
Database Management: Gain expertise in efficiently organizing, storing, and retrieving large amounts of data using modern database technologies.
Practical Applications: Work on real-world projects that simulate industry challenges, helping you apply theories to solve actual data problems.
Data Science Management: Learn strategies to manage data effectively within organizations, supporting better industry decision-making.
- Data Science Training in India provides a solid foundation for those aiming to break into the data science industry with practical tools and techniques. After completing a Data Science Course Online with Placement, freshers in India can expect a competitive salary as Data Science is one of the most in-demand fields in the country. The salary range can vary based on location, company, and specific skills, but the demand for skilled data professionals ensures attractive starting salaries.
- Salary Expectations for Freshers:
Starting Salary Range: Entry-level Data Scientists in India typically earn between 6,00,000 and 10,00,000 annually. The variation depends on the company, the city, and the specific skills acquired during the training.
Increased Earning Potential: As you gain more experience and expertise in machine learning, deep learning, data visualization, and programming languages (such as Python and R), salaries can increase to 12,00,000 - 18,00,000 within a few years.
Industry Differences: Different industries offer varying salaries. For instance, tech companies, fintech, and large consulting firms like Deloitte or Accenture tend to offer higher starting salaries, while industries such as healthcare or education may offer slightly lower but still competitive compensation.
Location Impact: Cities like Bangalore, Hyderabad, Mumbai, and Pune are known to have higher salary ranges due to the high concentration of tech companies and startups. In contrast, smaller cities or regions with a lower cost of living might offer salaries in the lower range.
Company Type: Large multinational companies and top tech firms often provide higher salaries, bonuses, and other benefits. Startups or smaller companies offer slightly lower salaries but compensate with other perks like flexible working hours or stock options.
- Data Science Course in India offers incredible career growth potential thanks to the high demand for skilled professionals. After completing a Data Science Online Training in India program, you can expect rapid career progression, moving from entry-level roles to more senior positions, depending on experience and skill development.
- Career Growth Highlights:
Rapid Advancement: With experience, freshers can move from junior roles like Data Analyst to positions like Data Scientist, Machine Learning Engineer, or Data Engineer.
Specialization Opportunities: As you grow, you can specialize in Natural Language Processing (NLP), deep learning, or AI, often with higher salaries and more challenging projects.
Leadership Roles: With technical expertise and business acumen, you can eventually move into managerial or leadership positions, such as Data Science Manager, Chief Data Officer (CDO), or Head of Data Analytics.
High Demand & Job Security: Data professionals enjoy job security and numerous career opportunities across different sectors due to the increasing reliance on data-driven decisions across all industries.
- At Croma Campus, known for its top-tier IT training, we offer one of the best Data Science Online Training with placement assistance designed to help you advance your career. This job-oriented online Enroll in Data Science Classes to gain the knowledge needed to tackle real-world data challenges using modern analytics tools.
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- What You Can Expect by Enrolling in Our Course:
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Professional Networking: Connect with industry experts and alums to grow your professional network, which is crucial for career development in Data Science.
Job Market Preparation: The Data Science Online Course in India is tailored to meet the needs of today's Data Science job market, ensuring you're ready to take on real-world challenges.
Skill Development: Focus on mastering the in-demand tools and techniques used by Data Scientists, such as Python, R, and machine learning algorithms.
Career Guidance: Get personalized mentorship and advice on successfully navigating the job search process in Data Science, both in India and internationally.
- Data Science is advancing quickly, creating numerous opportunities for aspiring professionals. At the heart of this growth are Best Online Data Science Course in India, particularly those offered online, which have become essential for individuals looking to start or further their careers in this domain.
- Key Insights into Data Science Education and Career Prospects:
Growing Relevance: As the demand for data-driven solutions increases, the range of Data Science courses has expanded, providing foundational and advanced knowledge.
Popularity of Online Courses: Online Data Science Classes have gained global recognition. They offer flexible schedules and a comprehensive curriculum that cater to a wide range of learners.
Accessibility of Education: Digital platforms have made Data Science education more accessible, enabling learners to gain high-quality education from anywhere.
Job Growth: The rise in Data Science-related job openings reflects the increasing demand for data professionals across industries.
Booming Job Market in India: The demand for Data Scientists is growing rapidly in India, making it an attractive and lucrative career option for many professionals.
Placement Guarantee Programs: Some Data Science courses provide education and placement assistance, helping students secure relevant positions in the field.
Specialized Roles: These courses cover essential roles like Data Scientist and Data Engineer, giving learners the knowledge and skills required for specific career paths in the industry.
- The current job market is experiencing an unprecedented demand for Data Science expertise, highlighting the importance of data in driving business decisions. This surge in demand is fueling a rise in Data Science job opportunities across various industries. A wide range of Data Science courses have been developed to meet this need, with online education playing a key role in making this knowledge accessible to a global audience.
- Here are some of the current trends in Data Science:
- Best Online Data Sciences Courses:
- In today's world, Data Science is becoming a vital field, and the best Data Science courses in India are helping shape future experts in this area. These courses teach the theory and practical skills needed to succeed in Data Science.
- Best Online Data Science Courses in India:
- Features of Data Science Online Courses:
- Data Science Certification Course:
- The best Data Science Online Classes don't just teach theorythey prepare you to solve real-world data problems. Whether you want to grow in your current job or explore something new, these courses are a great way to learn Data Science and build a successful career.
Data Science Courses: These courses provide a strong foundation in understanding and applying Data Science principles, preparing learners for the growing industry demand.
Immersive Online Learning: The best online Data Science courses offer an engaging learning experience, combining theoretical concepts with hands-on practical applications to enhance real-world readiness.
Surging Demand for Data Scientists in India: The demand for Data Scientist roles in India is skyrocketing, driven by the rapid growth of the digital economy and the increasing reliance on data analytics in business strategies.
Wide Industry Adoption: Data Science jobs are no longer confined to tech companies alone; industries such as healthcare, finance, retail, and manufacturing actively seek Data Science professionals to drive their data-driven decision-making.
Placement-Focused Courses: Data Science courses with placement assistance focus on bridging the gap between academic learning and employers' practical needs, increasing students' chances of securing industry-relevant positions.
Emerging Roles: The evolving roles of Data Engineers and Data Scientists are becoming more prominent in curricula, equipping students with the skills required for specialized career paths.
Complete Learning: These best Data Science courses in India cover everything you need to know about Data Science, including the latest tools and techniques used in the field.
Key Topics: The courses usually teach subjects like machine learning, analyzing data, and predicting outcomes, giving you a full understanding of the field.
Flexible Learning: Online courses allow you to study at your own pace, so you can fit learning around your job or other personal commitments.
Interactive: Many courses have live classes, discussion groups, and hands-on projects, making it easier to understand and apply the concepts.
Earn a Certificate: After completing the course, you can receive a certification, which will look great on your resume and can help with career opportunities.
- You May Also Read:
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CURRICULUM & PROJECTS
Data Science Certification Training
- Creation of Excel Sheet Data
- Range Name, Format Painter
- Conditional Formatting, Wrap Text, Merge & Centre
- Sort, Filter, Advance Filter
- Different type of Chart Creations
- Auditing, (Trace Precedents, Trace Dependents)Print Area
- Data Validations, Consolidate, Subtotal
- What if Analysis (Data Table, Goal Seek, Scenario)
- Solver, Freeze Panes
- Various Simple Functions in Excel(Sum, Average, Max, Min)
- Real Life Assignment work
- Advance Data Sorting
- Multi-level sorting
- Restoring data to original order after performing sorting
- Sort by icons
- Sort by colours
- Lookup Functions
- Lookup
- VLookup
- HLookup
- Subtotal, Multi-Level Subtotal
- Grouping Features
- Column Wise
- Row Wise
- Consolidation With Several Worksheets
- Filter
- Auto Filter
- Advance Filter
- Printing of Raw & Column Heading on Each Page
- Workbook Protection and Worksheet Protection
- Specified Range Protection in Worksheet
- Excel Data Analysis
- Goal Seek
- Scenario Manager
- Data Table
- Advance use of Data Tables in Excel
- Reporting and Information Representation
- Pivot Table
- Pivot Chat
- Slicer with Pivot Table & Chart
- Generating MIS Report In Excel
- Advance Functions of Excel
- Math & Trig Functions
- Text Functions
- Lookup & Reference Function
- Logical Functions & Date and Time Functions
- Database Functions
- Statistical Functions
- Financial Functions
- Functions for Calculation Depreciation
- SQL Server 2019 Installation
- Service Accounts & Use, Authentication Modes & Usage, Instance Congurations
- SQL Server Features & Purpose
- Using Management Studio (SSMS)
- Conguration Tools & SQLCMD
- Conventions & Collation
- SQL Database Architecture
- Database Creation using GUI
- Database Creation using T-SQL scripts
- DB Design using Files and File Groups
- File locations and Size parameters
- Database Structure modications
- SQL Server Database Tables
- Table creation using T-SQL Scripts
- Naming Conventions for Columns
- Single Row and Multi-Row Inserts
- Table Aliases
- Column Aliases & Usage
- Table creation using Schemas
- Basic INSERT
- UPDATE
- DELETE
- SELECT queries and Schemas
- Use of WHERE, IN and BETWEEN
- Variants of SELECT statement
- ORDER BY
- GROUPING
- HAVING
- ROWCOUNT and CUBE Functions
- Table creation using Constraints
- NULL and IDENTITY properties
- UNIQUE KEY Constraint and NOT NULL
- PRIMARY KEY Constraint & Usage
- CHECK and DEFAULT Constraints
- Naming Composite Primary Keys
- Disabling Constraints & Other Options
- Benets of Views in SQL Database
- Views on Tables and Views
- SCHEMA BINDING and ENCRYPTION
- Issues with Views and ALTER TABLE
- Common System Views and Metadata
- Common Dynamic Management views
- Working with JOINS inside views
- Need for Indexes & Usage
- Indexing Table & View Columns
- Index SCAN and SEEK
- INCLUDED Indexes & Usage
- Materializing Views (storage level)
- Composite Indexed Columns & Keys
- Indexes and Table Constraints
- Primary Keys & Non-Clustered Indexes
- Why to use Stored Procedures
- Types of Stored Procedures
- Use of Variables and parameters
- SCHEMABINDING and ENCRYPTION
- INPUT and OUTPUT parameters
- System level Stored Procedures
- Dynamic SQL and parameterization
- Scalar Valued Functions
- Types of Table Valued Functions
- SCHEMABINDING and ENCRYPTION
- System Functions and usage
- Date Functions
- Time Functions
- String and Operational Functions
- ROW_COUNT
- GROUPING Functions
- Why to use Triggers
- DML Triggers and Performance impact
- INSERTED and DELETED memory tables
- Data Audit operations & Sampling
- Database Triggers and Server Triggers
- Bulk Operations with Triggers
- Cursor declaration and Life cycle
- STATIC
- DYNAMIC
- SCROLL Cursors
- FORWARD_ONLY and LOCAL Cursors
- KEYSET Cursors with Complex SPs
- ACID Properties and Scope
- EXPLICIT Transaction types
- IMPLICIT Transactions and options
- AUTOCOMMIT Transaction and usage
- Overview of BI concepts
- Why we need BI
- Introduction to SSBI
- SSBI Tools
- Why Power BI
- What is Power BI
- Building Blocks of Power BI
- Getting started with Power BI Desktop
- Get Power BI Tools
- Introduction to Tools and Terminology
- Dashboard in Minutes
- Interacting with your Dashboards
- Sharing Dashboards and Reports
- Power BI Desktop
- Extracting data from various sources
- Workspaces in Power BI
- Data Transformation
- Query Editor
- Connecting Power BI Desktop to our Data Sources
- Editing Rows
- Understanding Append Queries
- Editing Columns
- Replacing Values
- Formatting Data
- Pivoting and Unpivoting Columns
- Splitting Columns
- Creating a New Group for our Queries
- Introducing the Star Schema
- Duplicating and Referencing Queries
- Creating the Dimension Tables
- Entering Data Manually
- Merging Queries
- Finishing the Dimension Table
- Introducing the another DimensionTable
- Creating an Index Column
- Duplicating Columns and Extracting Information
- Creating Conditional Columns
- Creating the FACT Table
- Performing Basic Mathematical Operations
- Improving Performance and Loading Data into the Data Model
- Introduction to Modelling
- Modelling Data
- Manage Data Relationship
- Optimize Data Models
- Cardinality and Cross Filtering
- Default Summarization & Sort by
- Creating Calculated Columns
- Creating Measures & Quick Measures
- What is DAX
- Data Types in DAX
- Calculation Types
- Syntax, Functions, Context Options
- DAX Functions
- Date and Time
- Time Intelligence
- Information
- Logical
- Mathematical
- Statistical
- Text and Aggregate
- Measures in DAX
- Measures and Calculated Columns
- ROW Context and Filter Context in DAX
- Operators in DAX - Real-time Usage
- Quick Measures in DAX - Auto validations
- In-Memory Processing DAX Performance
- How to use Visual in Power BI
- What Are Custom Visuals
- Creating Visualisations and Colour Formatting
- Setting Sort Order
- Scatter & Bubble Charts & Play Axis
- Tooltips and Slicers, Timeline Slicers & Sync Slicers
- Cross Filtering and Highlighting
- Visual, Page and Report Level Filters
- Drill Down/Up
- Hierarchies and Reference/Constant Lines
- Tables, Matrices & Conditional Formatting
- KPI's, Cards & Gauges
- Map Visualizations
- Custom Visuals
- Managing and Arranging
- Drill through and Custom Report Themes
- Grouping and Binning and Selection Pane, Bookmarks & Buttons
- Data Binding and Power BI Report Server
- Why Dashboard and Dashboard vs Reports
- Creating Dashboards
- Conguring a Dashboard Dashboard Tiles, Pinning Tiles
- Power BI Q&A
- Quick Insights in Power BI
- Custom Data Gateways
- Exploring live connections to data with Power BI
- Connecting directly to SQL Server
- Connectivity with CSV & Text Files
- Excel with Power BI Connect Excel to Power BI, Power BI Publisher for Excel
- Content packs
- Update content packs
- Introduction and Sharing Options Overview
- Publish from Power BI Desktop and Publish to Web
- Share Dashboard with Power BI Service
- Workspaces (Power BI Pro) and Content Packs (Power BI Pro)
- Print or Save as PDF and Row Level Security (Power BI Pro)
- Export Data from a Visualization
- Export to PowerPoint and Sharing Options Summary
- Understanding Data Refresh
- Personal Gateway (Power BI Pro and 64-bit Windows)
- Replacing a Dataset and Troubleshooting Refreshing
- Installation and Working with Python
- Understanding Python variables
- Python basic Operators
- Understanding the Python blocks.
- Python Comments, Multiline Comments.
- Python Indentation
- Understating the concepts of Operators
- Arithmetic
- Relational
- Logical
- Assignment
- Membership
- Identity
- Variables, expression condition and function
- Global and Local Variables in Python
- Packing and Unpacking Arguments
- Type Casting in Python
- Byte objects vs. string in Python
- Variable Scope
- Declaring and using Numeric data types
- Using string data type and string operations
- Understanding Non-numeric data types
- Understanding the concept of Casting and Boolean.
- Strings
- List
- Tuples
- Dictionary
- Sets
- Statements - if, else, elif
- How to use nested IF and Else in Python
- Loops
- Loops and Control Statements.
- Jumping Statements - Break, Continue, pass
- Looping techniques in Python
- How to use Range function in Loop
- Programs for printing Patterns in Python
- How to use if and else with Loop
- Use of Switch Function in Loop
- Elegant way of Python Iteration
- Generator in Python
- How to use nested Loop in Python
- Use If and Else in for and While Loop
- Examples of Looping with Break and Continue Statement
- How to use IN or NOT IN keyword in Python Loop.
- What is List.
- List Creation
- List Length
- List Append
- List Insert
- List Remove
- List Append & Extend using "+" and Keyword
- List Delete
- List related Keyword in Python
- List Reverse
- List Sorting
- List having Multiple Reference
- String Split to create a List
- List Indexing
- List Slicing
- List count and Looping
- List Comprehension and Nested Comprehension
- What is Tuple
- Tuple Creation
- Accessing Elements in Tuple
- Changing a Tuple
- Tuple Deletion
- Tuple Count
- Tuple Index
- Tuple Membership
- TupleBuilt in Function (Length, Sort)
- Dict Creation
- Dict Access (Accessing Dict Values)
- Dict Get Method
- Dict Add or Modify Elements
- Dict Copy
- Dict From Keys.
- Dict Items
- Dict Keys (Updating, Removing and Iterating)
- Dict Values
- Dict Comprehension
- Default Dictionaries
- Ordered Dictionaries
- Looping Dictionaries
- Dict useful methods (Pop, Pop Item, Str , Update etc.)
- What is Set
- Set Creation
- Add element to a Set
- Remove elements from a Set
- PythonSet Operations
- Frozen Sets
- What is Set
- Set Creation
- Add element to a Set
- Remove elements from a Set
- PythonSet Operations
- Python Syntax
- Function Call
- Return Statement
- Arguments in a function - Required, Default, Positional, Variable-length
- Write an Empty Function in Python -pass statement.
- Lamda/ Anonymous Function
- *args and **kwargs
- Help function in Python
- Scope and Life Time of Variable in Python Function
- Nested Loop in Python Function
- Recursive Function and Its Advantage and Disadvantage
- Organizing python codes using functions
- Organizing python projects into modules
- Importing own module as well as external modules
- Understanding Packages
- Random functions in python
- Programming using functions, modules & external packages
- Map, Filter and Reduce function with Lambda Function
- More example of Python Function
- Creation and working of decorator
- Idea and practical example of generator, use of generator
- Concept and working of Iterator
- Python Errors and Built-in-Exceptions
- Exception handing Try, Except and Finally
- Catching Exceptions in Python
- Catching Specic Exception in Python
- Raising Exception
- Try and Finally
- Opening a File
- Python File Modes
- Closing File
- Writing to a File
- Reading from a File
- Renaming and Deleting Files in Python
- Python Directory and File Management
- List Directories and Files
- Making New Directory
- Changing Directory
- Threading, Multi-threading
- Memory management concept of python
- working of Multi tasking system
- Different os function with thread
- SQL Database connection using
- Creating and searching tables
- Reading and Storing cong information on database
- Programming using database connections
- Working With Excel
- Reading an excel le using Python
- Writing to an excel sheet using Python
- Python| Reading an excel le
- Python | Writing an excel le
- Adjusting Rows and Column using Python
- ArithmeticOperation in Excel le.
- Play with Workbook, Sheets and Cells in Excel using Python
- Creating and Removing Sheets
- Formatting the Excel File Data
- More example of Python Function
- Check Dirs. (exist or not)
- How to split path and extension
- How to get user prole detail
- Get the path of Desktop, Documents, Downloads etc.
- Handle the File System Organization using OS
- How to get any les and folder's details using OS
- What is Machine Learning
- Machine Learning Use-Cases
- Machine Learning Process Flow
- Machine Learning Categories
- What is Time Series Analysis
- Importance of TSA
- Components of TSA
- White Noise
- AR model
- MA model
- ARMA model
- ARIMA model
- Stationarity
- ACF & PACF
- What is Exploratory Data Analysis
- EDA Techniques
- EDA Classification
- Univariate Non-graphical EDA
- Univariate Graphical EDA
- Multivariate Non-graphical EDA
- Multivariate Graphical EDA
- Heat Maps
- Overview of Text Mining
- Need of Text Mining
- Natural Language Processing (NLP) in Text Mining
- Overview of Text Mining
- Need of Text Mining
- Natural Language Processing (NLP) in Text Mining
- Applications of Text Mining
- OS Module
- Reading, Writing to text and word files
- Setting the NLTK Environment
- Accessing the NLTK Corpora
- Tokenization
- Frequency Distribution
- Different Types of Tokenizers
- Bigrams, Trigrams & Ngrams
- Stemming
- Lemmatization
- Stopwords
- POS Tagging
- Named Entity Recognition
- Syntax Trees
- Chunking
- Chinking
- Context Free Grammars (CFG)
- Automating Text Paraphrasing
- Machine Learning: Brush Up
- Bag of Words
- Count Vectorizer
- Term Frequency (TF)
- Inverse Document Frequency (IDF)
- Introduction to TensorFlow 2.x
- Installing TensorFlow 2.x
- Defining Sequence model layers
- Activation Function
- Layer Types
- Model Compilation
- Model Optimizer
- Model Loss Function
- Model Training
- Digit Classification using Simple Neural Network in TensorFlow 2.x
- Improving the model
- Adding Hidden Layer
- Adding Dropout
- Using Adam Optimizer
- What is Deep Learning
- Curse of Dimensionality
- Machine Learning vs. Deep Learning
- Use cases of Deep Learning
- Human Brain vs. Neural Network
- What is Perceptron
- Learning Rate
- Epoch
- Batch Size
- Activation Function
- Single Layer Perceptron
- What is NN
- Types of NN
- Creation of simple neural network using tensorflow
- Image Classification Example
- What is Convolution
- Convolutional Layer Network
- Convolutional Layer
- Filtering
- ReLU Layer
- Pooling
- Data Flattening
- Fully Connected Layer
- Predicting a cat or a dog
- Saving and Loading a Model
- Face Detection using OpenCV
- Introduction to Vision
- Importance of Image Processing
- Image Processing Challenges – Interclass Variation, ViewPoint Variation, Illumination, Background Clutter, Occlusion & Number of Large Categories
- Introduction to Image – Image Transformation, Image Processing Operations & Simple Point Operations
- Noise Reduction – Moving Average & 2D Moving Average
- Image Filtering – Linear & Gaussian Filtering
- Disadvantage of Correlation Filter
- Introduction to Convolution
- Boundary Effects – Zero, Wrap, Clamp & Mirror
- Image Sharpening
- Template Matching
- Edge Detection – Image filtering, Origin of Edges, Edges in images as Functions, Sobel Edge Detector
- Effect of Noise
- Laplacian Filter
- Smoothing with Gaussian
- LOG Filter – Blob Detection
- Noise – Reduction using Salt & Pepper Noise using Gaussian Filter
- Nonlinear Filters
- Bilateral Filters
- Canny Edge Detector - Non Maximum Suppression, Hysteresis Thresholding
- Image Sampling & Interpolation – Image Sub Sampling, Image Aliasing, Nyquist Limit, Wagon Wheel Effect, Down Sampling with Gaussian Filter, Image Pyramid, Image Up Sampling
- Image Interpolation – Nearest Neighbour Interpolation, Linear Interpolation, Bilinear Interpolation & Cubic Interpolation
- Introduction to the dnn module
- Deep Learning Deployment Toolkit
- Use of DLDT with OpenCV4.0
- OpenVINO Toolkit
- Introduction
- Model Optimization of pre-trained models
- Inference Engine and Deployment process
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FAQ's
The main reason to choose the Online Data Science Course in India from the Croma Campus is so that you can grow your skills under the guidance of the corporate trainers that help you too gain the essential skills and knowledge to meet the demands of the organization with perfect solutions.
The Data Science Online Training in India from Croma Campus will help you to learn from the practical and theoretical formats and will also help you to learn from the real time-based projects that will upgrade your profile needed by the fortune organizations.
The Online Data Science Course in India with Certification can be done with Croma campus offering various ways to learn. You can choose any service from:
- Instructor Training
- Online Training
- Corporate Training
- Self-paced Training
- 1 on 1 Training
It takes around 5 to 6 months to learn the course from the Online Data Science Course in India. Also, it depends upon the learner. On an average this time is perfect to learn the course.
To start learning Data Science Online Certification Course in India you can contact to: Email: Info@cromacampus.com Contact no.: +91-9711526942 / +91-120-4155255
The duration of a Data Science course typically ranges from a few weeks for introductory programs to 2-3 years for in-depth degree courses.
Data Science course fees in India vary, starting from around INR 10,000 for basic courses to over INR 2,00,000 for comprehensive and specialized programs.
Topics in a Data Science online course usually include statistics, machine learning, Python programming, data visualization, and big data analysis.
A Data Scientist is a professional skilled in extracting insights and knowledge from data, using techniques in statistics, machine learning, and data analysis.
Yes, this Data Science course can be suitable for freshers, as many courses are designed to accommodate beginners with no prior experience.
A Data Science Management course focuses on combining data science skills with management principles, targeting professionals who oversee data-driven projects and teams.
To enroll in the best Data Science courses, research top-rated programs online or through academic institutions, and follow their application or registration process.
Yes, a Data Scientist job is often categorized under IT, as it involves working with technology and data systems, though it also encompasses statistical and analytical skills.
Eligibility for a Data Science online course varies, but generally, anyone with a keen interest in data and basic analytical skills can enroll. Some advanced courses might require prior knowledge in statistics or programming.
Croma Campus is the Best Data Science Training Institute in India from last two decade.
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Training Features
Instructor-led Sessions
The most traditional way to learn with increased visibility,monitoring and control over learners with ease to learn at any time from internet-connected devices.
Real-life Case Studies
Case studies based on top industry frameworks help you to relate your learning with real-time based industry solutions.
Assignment
Adding the scope of improvement and fostering the analytical abilities and skills through the perfect piece of academic work.
Lifetime Access
Get Unlimited access of the course throughout the life providing the freedom to learn at your own pace.
24 x 7 Expert Support
With no limits to learn and in-depth vision from all-time available support to resolve all your queries related to the course.
Certification
Each certification associated with the program is affiliated with the top universities providing edge to gain epitome in the course.
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Data Science
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