Join Our 100% Job-Guaranteed Data Science Full Stack Course in OMR. We Provide Quality Data Science Full Stack training with an affordable Cost in OMR. Our Data Science Full Stack Course Syllabus covers Python programming, statistics, data wrangling, data visualization, machine learning, deep learning, big data tools, cloud deployment, and real-world project implementation. At Softlogic Systems, you’ll earn globally recognized certifications, build real-time projects, and receive complete placement assistance to launch a successful career in your chosen field.
Data Science Fullstack Training In Omr
4.80
(6361)
DURATION
4 Months
EMI
0% Interest
Mode
Live Online / Offline
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Course Syllabus
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Fees, Duration & Batch Timings for Data Science Fullstack Course
Hands On Training
3-5 Real Time Projects
60-100 Practical Assignments
3+ Assessments / Mock Interviews
July 2026
Week days
(Mon-Fri)
Online/Offline
2 Hours Real Time Interactive Technical Training
1 Hour Aptitude
1 Hour Communication & Soft Skills
(Suitable for Fresh Jobseekers / Non IT to IT transition)
Course Fee
July 2026
Week ends
(Sat-Sun)
Online/Offline
4 Hours Real Time Interactive Technical Training
(Suitable for working IT Professionals)
Course Fee
Save up to 20% in your Course Fee on our Job Seeker Course Series
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Syllabus of Data Science Fullstack Course
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CORE PYTHON
- Python Introduction & history
- Color coding schemes
- Salient features & flavors
- Application types
- Language components (variables, literals, operators, keywords…)
- String handling management
1. String operations – indexing, slicing, ranging
2. String methods – concatenation, repetition, formatting
3. Supporting functions - Native data types
1. List
2. Tuple
3. Set
4. Dictionary - Decision making statements
1. If
2. If…else
3. If…elif…else - Looping statements
1. For loop
2. While loop - Function types
1. Built-in functions
2. Math functions
3. User defined functions
4. Recursive functions
5. Lambda functions - OOPs
1. Classes and objects
2. __init__ constructor
3. Self-keyword
4. Data abstraction
5. Data encapsulation
6. Polymorphism
7. Inheritance - Exception handling
1. Error vs exception
2. Types of error
3. User defined exception handling
4. Exception handler components
5. Try block, except block, finally block - File handling
1. How to create a txt file using python
2. File access modes
3. Reading and writing data to a txt file
4. Data operations
DATA SCIENCE PHASE 1
- Working with PANDAS & NUMPY
1. PANDAS – data analysis intro
2. PANDAS – data structures
3. Series creation types
4. Data Frame creation types
5. Accessing data from Series and DataFrame
6. Data merging - Working with PANDAS & NUMPY
1. Data mapping
2. Finding duplicates
3. Removing duplicates
4. Describing data
5. Finding null values
6. Group by function
7. Sort values
8. Statistical functions
9. Reading and writing data from CSV
10. Data operations on CSV file
11. Basic visualizations
12. NUMPY array processing intro
13. Types of ndarray - Numpy attributes
1. ndim
2. shape
3. size
4. type - Shape manipulations
1. Ravel
2. Reshape
3. Resize
4. Hsplit
5. Vstack - Numpy additional functions
1. Tile
2. Eye
3. Zeros
4. Ones
5. Diag
6. arange
7. New axis addition
8. Random number generation
DATA SCIENCE PHASE 2
- Data science terminologies
- Exploratory data analysis intro
- Types of machine learning algorithms
- Classification and regression intro
- Prediction and analysis techniques to be used in ML
- MATPLOTLIB – data visualization
1. Histogram
2. Pdf
3. Adding axes
4. Adding grid
5. Adding label
6. Adding ticks
7. Setting limits
8. Adding legend - MATPLOTLIB plotting
1. Bar chart
2. Pie chart
3. Heat map
4. Box plot
5. Scatter plot
6. 3d plot - SEABORN – advanced color palette visualization
1. Bar chart
2. Pie chart
3. Dist plot
4. Pair plot
5. Reg plot
6. Count plot
7. Swarmplot
8. Heat map
9. Scatter plot
10. Lm plot
EDA – MACHINE LEARNING –WORKING WITH SCIKIT-LEARN
- Machine learning algorithm types
1. Supervised learning
2. Unsupervised learning
3. Ensemble learning technique - Working flow of dataset
1. Loading necessary modules
2. Loading dataset
3. Feature scaling
4. Feature extraction
5. Data standardization
6. Data normalization
7. Data manifesting
8. Model creation
9. Fitting data models
10. Model prediction - ML algorithms with live demo and mathematical intuition
1. Linear regression
2. Logistic regression
3. Naïve bayes classifier
4. KNN (K nearest neighbor)
5. KMC (K means clustering)
6. Support vector machines
7. Principal component analysis
8. Decision tree
9. Random forest
10. XGBoost
DEEP LEARNING & AI
- Neural networks introduction
- Brain activation functions and layer components
- Neural network terminologies of ANN, CNN, RNN
1. Models
2. Initializers
3. Optimizers
4. Layers
5. Activation functions
6. Loss functions
7. Metrics
8. Model compilations
9. Model evaluation
10. Max pooling layers
11. Edge filters
12. Back propagations
13. Early stopping
14. Epoch - Datasets to be used for MLP,ANN, CNN,RNN
1. Boston house prediction
2. CIFAR10
3. CIFAR100
4. MNIST
5. FASHION MNIST
6. IMDB Movie review analysis - NLP (Natural Language Processing)
1. NLTK
2. NLTK
3. SPACY - COMPUTER VISION
1. Digital Image Processing using CV2 library
2. LIVE PROJECTS
Objectives of Data Science Fullstack Training
The objectives of learning Data Science Fullstack Training include
- Master frontend and backend development.
- Learn data analysis techniques.
- Build machine learning skills.
- Develop proficiency in web development.
- Gain practical experience with projects.
- Ensure alignment with industry standards.
- Obtain certifications and support for placements.
Why Softlogic Systems is the Best Choice for Data Science Fullstack Training – Learn, Practice, and Get Placed!
Online & Offline Training Options
Learn at your convenience with flexible classroom and live online training.
Learn from 100+ Real-Time Developers
Get trained by industry professionals with years of hands-on experience.
Hands-on Projects & Codeathons
Practice with real-time projects and coding challenges to build confidence.
0% EMI Fee Options
Pay your course fees flexibly with easy EMI plans at zero interest.
Resume & Interview Support
Get expert help with resume building, mock interviews, and soft skills.
Placement with Top IT Firms
Access placement opportunities with leading MNCs and IT companies.
1000+ Hiring Partners
Benefit from Softlogic’s strong recruiter network for faster job placement.
No Backdoor Jobs
We ensure only genuine placement opportunities with trusted companies.
Want to Speak to a Trainer about Data Science Fullstack?Request a Free Callback
Highlights of Data Science Fullstack Course
What is Data Science Fullstack?
Data Science Fullstack entails proficiency in both frontend and backend tasks of data science, including data analysis, machine learning, and web development. It enables professionals to handle the entire project lifecycle, from data processing to building and deploying interactive applications.
What are the reasons for learning Data Science Fullstack?
Learning Data Science Fullstack has many advantages:
- Versatility: It teaches both frontend and backend tasks, making you adaptable.
- Independence: You can manage projects from start to finish.
- Career Opportunities: There are many job options.
- Problem-Solving: You’ll solve problems more effectively.
- Real-World Use: You’ll create practical solutions.
What are the prerequisites for learning Data Science Fullstack?
Prerequisites for learning Data Science Fullstack include basic programming skills in Python or R, knowledge of data analysis techniques, and familiarity with HTML, CSS, and JavaScript for frontend development.
Our Data Science Fullstack Training in OMR is suitable for:
- Students
- Professionals seeking a career change
- IT professionals aiming to enhance their skills
- Enthusiastic programmers
- Job Seekers
What are the course fees and duration?
For our Data Science Fullstack Training in OMR, program fees vary based on the level (basic, intermediate, or advanced) and format (online or in-person). Typically, fees range from 50,000 INR to 65,000 INR for a 4-month duration, inclusive of international certification. For precise details, contact our institute directly.
What are some job roles related to Data Science Fullstack?
Some job roles related to Data Science Fullstack are:
- Data Scientist: Analyzes data and builds models.
- Fullstack Developer: Designs and develops applications.
- Machine Learning Engineer: Implements machine learning.
- Data Engineer: Builds data pipelines.
- Data Analyst: Extracts insights from data.
- Business Intelligence Developer: Creates visualization tools.
What is the salary range for Data Science Fullstack Engineer?
A fresher Data Scientist, with less than three years of experience, typically earns an average annual salary of ₹9,80,000 Lakhs. A mid-career Data Scientist, with 4-9 years of experience, earns around ₹16,00,000 Lakhs per year on average, while an experienced Data Scientist, with 10-20 years of experience, earns an average annual salary of ₹23,00,000 Lakhs.
List a few Data Science Fullstack real-time applications.
Here are some examples of real-time applications made with Data Science Fullstack:
- Predictive Maintenance: Forecasting equipment failures for timely maintenance.
- Personalized Recommendations: Suggesting products based on user behavior.
- Fraud Detection: Spotting fraudulent activities in transactions.
- Health Monitoring: Tracking and analyzing health data in real-time.
- Smart Manufacturing: Optimizing production with data and IoT sensors.
- Traffic Management: Improving flow and reducing congestion with data analysis.
- Energy Optimization: Minimizing energy wastage and improving efficiency in power grids.
Boost Your Skills with Our Data Science Fullstack Training Experts
Our Mentors are from Top Companies like:
- Our Data Science Fullstack Training in OMR is led by experienced trainers with extensive industry knowledge.
- Trainers are proficient in frontend and backend technologies, including Data Science programming and Spring Boot.
- They possess expertise in essential web development concepts such as HTML, CSS, Data ScienceScript, and Bootstrap frameworks.
- Trainers excel at simplifying complex concepts, ensuring comprehensive understanding among students.
- Drawing from real-world application development experience, they offer valuable practical insights to students.
- Committed to continuous learning, trainers stay updated with the latest trends and technologies in Data Science Full Stack Development.
- They prioritize building students’ foundational knowledge and practical skills for professional success.
- Trainers foster an inclusive learning environment where collaboration and inquiry are encouraged.
- Their passion for sharing knowledge and expertise motivates students to excel in their careers.
- With dedication and support, trainers empower students to become proficient Data Science Full Stack Developers.
Want to Speak to a Trainer about Data Science Fullstack?Request a Free Callback
What Modes of Training are available for Data Science Fullstack Course?
Offline / Classroom Training
A Personalized Learning Experience with Direct Trainer Engagement!
- Direct Interaction with the Trainer
- Clarify doubts then and there
- Airconditioned Premium Classrooms and Lab with all amenities
- Codeathon Practices
- Direct Aptitude Training
- Live Interview Skills Training
- Direct Panel Mock Interviews
- Campus Drives
- 100% Placement Support
Online Training
Instructor Led Live Training! Learn at the comfort of your home
- No Recorded Sessions
- Live Virtual Interaction with the Trainer
- Clarify doubts then and there virtually
- Live Virtual Interview Skills Training
- Live Virtual Aptitude Training
- Online Panel Mock Interviews
- 100% Placement Support
Corporate Training
Blended Delivery model (both Online and Offline as per Clients’ requirement)
- Industry endorsed Skilled Faculties
- Flexible Pricing Options
- Customized Syllabus
- 12X6 Assistance and Support
Want to Master your Skills in Data Science Fullstack?GET Free Consultation
Certifications
Take your career to new heights with Softlogic's software training certifications.
Improve your abilities to get access to rewarding possibilities
Improve your abilities to get access to rewarding possibilities
Earn Your Certificate of Completion
Validate your achievements with Softlogic's Certificate of Completion, verifying successful fulfillment of all essential components.
Take Your Career to the Next Level with Certifications
Get a certifications through our training programs to gain a competitive edge in the industry.
Stand Out from the Crowd with Codethon Certificate
Verify the authenticity of your real-time projects with Softlogic's Codethon certificate.
Hands-on Project Practices in Data Science Fullstack Course
Customer Churn Prediction
Social Media Sentiment Analysis
Energy Consumption Optimization
Traffic Management System
Smart Manufacturing Optimization
Healthcare Monitoring Solution
Fraud Detection System
E-commerce Recommendation Engine
Predictive Maintenance System
The SLA Way to Get Placed in Top IT Companies
Enrollment
Technology Training
Coding Practices
Realtime Projects
Realtime Projects
Placement Training
Aptitude Training
Interview Skills
Interview Skills
Panel Mock
Interview
Unlimited
Interviews
Interview
Feedback
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See More ReviewsPlacement Support for a Data Science Fullstack Job
Genuine Placements. No Backdoor Jobs at Softlogic Systems.
Aptitude Training
from Day 1
Interview Skills
from Day 1
Softskills Training
from Day 1
Build Your Resume
Build your LinkedIn Profile
Build your GitHub
digital portfolio
Panel Mock Interview
Unlimited Interviews until you get placed
Life Long Placement Support at no cost
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FAQs
Is full-stack useful for data science?
Yes, Full-stack skills are beneficial for data science. They offer a complete understanding of both frontend and backend technologies, allowing data scientists to create end-to-end applications, visualize data effectively, deploy quickly, integrate with backend systems, and collaborate efficiently.
Does data science require heavy coding?
Yes, data science usually involves coding, but the amount required can vary. Tasks like data cleaning and building models often require significant coding, while others, like visualization, may need less. However, knowing languages like Python or R is crucial for most data science jobs.
Does data science require SQL?
Yes, data science often involves SQL for querying and manipulating databases. It’s crucial for tasks like data extraction and analysis.
Is data scientist a stressful job?
Data science offers varied stress levels based on project demands and individual preferences, with some finding it less stressful due to its problem-solving nature and data-centric focus.
Can I still join job placement events if I already have a job offer?
Definitely! We offer ongoing placement assistance to help candidates achieve their career goals. Contact our career advisor to arrange a free demo for the leading Data Science Fullstack course in OMR, featuring placement support.
Does SLA support EMI options?
Yes, SLA does have an EMI option with 0% interest.
How does the placement team at SLA support us?
The placement team at SLA enhances your job prospects by providing comprehensive support. Whether you’re a certified student looking to switch careers or entering the workforce for the first time, you’ll receive extensive assistance through our placement services. SLA offers the following premium services as part of our placement support:
- Resume building
- Career guidance and advising
- Interview practice sessions
- Career expos
What accreditation will I get once the course is completed?
Upon completion of SLA’s training, you will be awarded with globally recognized course completion certificates from SLA, renowned IBM certificates, and Codeathon certificates, validating your real-time project experience.
What are the different payment options available?
We accept all sort of major payment methods like cash, credit cards (Visa, Maestro, Master card), Netbanking, etc
I have more queries?
Please contact our course counselor by call or Whatsapp at +91 86818 84318. As an alternative, you can use our Website chat, Website form, or email us at enquiry@softlogicsys.in
Additional Information for
the Data Science Fullstack Course
Future Career Opportunities
The Data Science Fullstack Course presents promising prospects for career advancement. As industries adopt data-driven strategies, skilled professionals are increasingly sought after to derive insights and inform decision-making. Graduates can expect a wide range of opportunities across sectors, from healthcare and finance to marketing and technology.
Technological Advancements
Advancements in technology, including machine learning, artificial intelligence, and big data analytics, continue to shape the field of data science. As these technologies evolve, professionals equipped with Fullstack skills will play a crucial role in leveraging data for innovation and problem-solving.
Continuous Learning and Innovation
Staying updated with emerging trends and technologies is essential for success in data science. Graduates of the Data Science Fullstack Course are encouraged to embrace lifelong learning to remain at the forefront of the field, contributing to ongoing innovation and driving future advancements.
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