Softlogic is one of the Top Training institutes for Data Science FullStack. Learn how to use Data Science FullStack, from beginner basics to advanced techniques. 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. We offer a Data Science FullStack Course with Placement Assistance, Mock interviews, Resume building, and certification.
Data Science Full Stack Course
4.50
(5236)
DURATION
4 Months
EMI
0% Interest
Mode
Live Online / Offline
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Fees, Duration & Batch Timings for Data Science Full Stack 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 Full Stack 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 Full Stack Training
- Learn Core Python for a strong programming foundation.
- Understand Machine Learning algorithms and their uses.
- Explore Deep Learning and its practical applications.
- Discover Artificial Intelligence and its real-world uses.
- Get hands-on with essential data science tools like Numpy, Pandas, Matplotlib, and Seaborn.
- Gain practical experience through real-world projects.
Why Softlogic Systems is the Best Choice for Data Science Full Stack 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 Full Stack?Request a Free Callback
Highlights of Data Science Full Stack Course
What is the Data Science Full Stack Developer course?
The Data Science Full Stack Developer course teaches you all the skills you need for a career in data science. You’ll learn Core Python, Machine Learning, Deep Learning, and Artificial Intelligence, as well as the tools and technologies used in the field. Through hands-on projects, you’ll gain the experience needed for entry-level roles in data science. The course is designed to spark your interest in data science and prepare you for success in this fast-growing field.
What are the reasons for learning Data Science Full Stack Developer?
There are several compelling reasons to learn Data Science Full Stack Developer:
- Abundant Career Options: Data Science Full Stack Developers are highly sought-after, with diverse job opportunities in various sectors.
- Adaptable Skills: These skills can be applied across different areas of data science, such as analysis, machine learning, and big data handling.
- Lucrative Salaries: Data Science Full Stack Developers often earn competitive pay due to their specialized expertise and high demand.
- Intellectually Stimulating: Developers tackle complex challenges using data, making their work engaging and innovative.
- Meaningful Impact: By analyzing data, developers contribute significantly to business decisions and strategies.
- Promising Future: With the growing reliance on data-driven insights, the demand for these developers is expected to continue rising, providing ample career growth opportunities.
What are the prerequisites for learning Data Science Full Stack Developer?
The Data Science Full Stack Developer course is open to all freshers interested in Data Science, without any prerequisites. It’s suitable for recent graduates or professionals looking for a career change. The course provides the essential skills and knowledge needed to succeed in Data Science, regardless of your background.
What are the course fees and duration?
The fees for our Data Science Full Stack Developer Job Seeker Program vary based on the program level (basic, intermediate, or advanced) and the course format (online or in-person). On average, the fees for the Data Science Full Stack Developer Job Seeker Program range from 50,000 INR to 65,000 INR for a duration of 4 months, which includes international certification. For accurate and current information regarding fees, duration, and certification, please reach out to our premier Data Science Full Stack Developer Training Institute directly.
What are some job roles related to Data Science Full Stack Developer?
Some job roles related to Data Science Developer include:
- Data Scientist: Analyzing data to find insights.
- Data Engineer: Building and managing data pipelines.
- Machine Learning Engineer: Developing machine learning models.
- Big Data Developer: Working with large-scale data processing.
- Business Intelligence Analyst: Analyzing data for business decisions.
- Data Analyst: Examining data for trends and reports.
- Data Architect: Designing data management solutions.
- Full Stack Developer: Creating front-end and back-end for data applications.
What is the salary range for a Data Science Full Stack Developer?
As per Ambition Box, a Data Scientist fresher with less than three years of experience earns an average salary ranging from ₹2.5 Lakhs to ₹5 Lakhs per year. A mid-career Data Scientist with 4-9 years of experience earns an average salary of ₹9 Lakhs per year, while an experienced Data Scientist with 10-20 years of experience earns an average salary of ₹15 Lakhs per year.
List a few Data Science Full Stack Development real-time applications.
Data Science Full Stack Development has various real-world applications, including:
- Finance: Using real-time data analysis for detecting fraud in banking transactions and analyzing stock market trends.
- Healthcare: Implementing real-time monitoring systems for patients and providing personalized treatment recommendations.
- E-commerce: Utilizing real-time data for suggesting products to customers and managing inventory effectively.
- Transportation: Employing real-time data for monitoring traffic conditions and optimizing routes for logistics.
- Manufacturing: Implementing real-time quality control measures and predicting maintenance needs for machinery.
Boost Your Skills with Our Data Science Full Stack Training Experts
Our Mentors are from Top Companies like:
- Our trainers have strong educational backgrounds, specializing in computer science, data science, or related fields.
- They possess extensive industry experience, having worked on real-world projects in data science and full-stack development.
- Many trainers hold certifications in data science, machine learning, and full-stack development.
- With a background in teaching, they excel in explaining complex concepts effectively.
- Our trainers specialize in various aspects of data science and full-stack development.
- They are proficient in tools such as Python, R, Java, SQL, and data analysis and visualization tools.
- Dedicated to learning continuously, they keep themselves updated with the latest trends.
- Providing mentorship and guidance, our trainers help students navigate the course and develop their skills.
- Their exceptional communication skills aid in engaging students and facilitating interactive learning sessions.
- Above all, our trainers are passionate about teaching and dedicated to student success.
Want to Speak to a Trainer about Data Science Full Stack?Request a Free Callback
What Modes of Training are available for Data Science Full Stack 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 Full Stack?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 Full Stack Course
Marketing Analytics
Energy Management
E-commerce Personalization
Environmental Monitoring
Transportation and Logistics
Manufacturing Optimization
Agriculture
Cybersecurity
Insurance Risk Assessment
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
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Interview
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IT Career
Placement Support for a Data Science Full Stack 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
What is SLA’s Job Seeker program?
SLA’s Job Seeker program is designed to help freshers enter the IT industry quickly. The program offers a syllabus tailored for each fresher, based on the expectations of IT clients. It focuses on providing a combination of technologies in full-stack development, which enhances the fresher’s chances of securing a job in IT.
Does data science have future?
Yes, data science has a bright future. As businesses and industries generate more data, the demand for skilled data scientists will increase. Data science is already used in various fields and with advancements in technology, its role will become more crucial in decision-making and innovation.
What skills are required for data scientist?
Data scientists need to be skilled in programming languages like Python, R, and SQL, and have a good understanding of statistics and machine learning. They should also be adept at cleaning and organizing data, visualizing data effectively, and have knowledge of the industry they work in. Strong problem-solving, communication, curiosity, and creativity are also essential skills.
What does a data scientist do?
A data scientist analyzes data to find useful information and solve problems. They use statistics, machine learning, and programming to clean, process, and study large datasets. Data scientists also create visualizations and share their findings with others to help organizations make decisions based on data.
Is data science need coding?
Yes, data science requires coding skills. Data scientists use programming languages like Python, R, and SQL to clean, process, analyze, and visualize data. Coding is essential for data scientists to manipulate data, build machine learning models, and extract insights from datasets.
What is the salary of full stack data scientist?
The salary for a full-stack data scientist can differ based on variables like experience, location, and the company. However, on average, a full-stack data scientist with less than three years of experience can earn around 3 lakhs per annum. With increasing experience and expertise, their salary has the potential to rise substantially.
Does SLA offer any certification or badge for Data Science Full stack developer Jobseeker program?
Yes, SLA offers IBM-accredited certifications upon successful completion of their Java Full stack developer training course.
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 methods of payment are available?
We accept all major payment methods. Cash, debit cards, credit cards (including Master, Visa, and Maestro), net banking, UPI, 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 Full Stack Course
Promising Career Paths
The Data Science Full Stack Developer Program offers bright career opportunities. With businesses increasingly relying on data-driven decisions, there’s a growing demand for professionals skilled in both data science and full-stack development. Graduates can explore roles like data scientist, data engineer, or full-stack developer, among others, thanks to the program’s comprehensive curriculum and hands-on learning.
Adaptability Across Industries
This program’s versatility is a big plus, as data science and full-stack development skills are valuable in various industries. Graduates can work in finance, healthcare, e-commerce, and more, giving them the flexibility to switch between industries as their interests evolve. Real-world projects ensure they’re well-prepared for diverse job markets.
Continuous Learning and Growth
The Data Science Full Stack Developer Program lays a strong foundation for lifelong learning and career advancement in the tech field. By mastering data science techniques, programming languages, and full-stack tools, graduates can adapt to new technologies. Emphasizing ongoing learning, the program prepares graduates to thrive in a dynamic tech landscape.
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