Data Science Course with Certification & Placement

4.40/5.0

(359)

Live Online & Classroom Training

No Cost EMI

Trying to get into Data Science but not sure where to start? Instead of jumping between random tutorials, this course gives you a clear path — from basics to working with real data.

You’ll learn how to use tools like Python and SQL, spend time on datasets, and understand how things actually work in real situations. It’s not just about concepts — you’ll be doing the work, step by step.

As you move forward, you’ll also get guidance on projects and interviews, so when you start applying for jobs, you’re not going in blind. The idea is simple: help you build real skills and feel ready to take that next step.

Download Course & Placement Details

Have Queries? Ask our Experts

+91 63742 083445

Upcoming Batches

Hands On Training

Real-time projects & assignments

Mock interviews & assessments

Online & classroom learning modes

April 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

April 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

Learn More

Quick Enquiry

Placement

Life-time Unlimited Placement Support

Learning

Industry-Oriented Training

Timings

Convenient Hours

Mode

Online & Classroom

Certification

Global Certification Programs

We Tie-Up with 1000+ Leading IT and MNC Companies

SLA's Hiring and Placement Partner: Birlasoft

SLA's Hiring and Placement Partner: Observeai

SLA's Hiring and Placement Partner: GlobalLogic

SLA's Hiring and Placement Partner: Tredence

SLA's Hiring and Placement Partner: Acs Solutions

SLA's Hiring and Placement Partner: Napier

SLA's Hiring and Placement Partner: Intellect

SLA's Hiring and Placement Partner: Highradius

SLA's Hiring and Placement Partner: Latent View

SLA's Hiring and Placement Partner: Prodapt

SLA's Hiring and Placement Partner: Valuemomentum

SLA's Hiring and Placement Partner: Tanla

This Course Includes

Free Demo Class — experience the training before you commit
Flexible Fee & No-Cost EMI — start learning without financial stress
Soft Skills & Communication Training — because technical skills alone won’t get you the job
Placement Support & Interview Preparation — from resume to offer letter, we’ve got you
Globally Recognised Course Completion Certificate
Real-Time Projects & Codeathon Experience
Training by IT Professionals with Real Industry Experience

Talk to a Course Advisor

Expected Criteria for Assured Placement

Our placement support process is designed to help students prepare for and participate in interview opportunities after completing their training. To make the most of placement support, students are expected to actively engage in the learning and preparation process.

Placement Support Guidelines

Successful completion of the course curriculum and required projects
Successful completion of the course curriculum and required projects
Completion of resume preparation, soft skills, and interview readiness training
Regular updates of technical skills based on interview feedback
Participation in scheduled interview opportunities as per individual readiness
Continuous learning and improvement based on recruiter feedback

Students receive ongoing guidance from the placement team to help improve performance and readiness for future opportunities.

How Placement Support Works

Placement support includes interview opportunities, career guidance, and skill improvement support provided on an ongoing basis. Interview participation and career decisions remain with the student and depend on individual readiness, performance, and available opportunities. Job placement is not guaranteed.

Have Queries? Ask our Experts

+91 63742 83445

SLA’s Career-Oriented Training & Placement Support Process

1

Industry-Focused Training

2

Expert-Led Mentorship

3

Assignments & Real-Time Projects

4

Mock Interviews & Feedback

5

Mock Interviews & Feedback

6

Placement Support & Interview Opportunities

Key Features of the Data Science Certification Course

Comprehensive Curriculum: Covers the core areas of data science, including Python, statistics, machine learning, and data analysis, so you understand how everything fits together.
Hands-On & Practical Learning: You’ll work on real datasets and exercises, which helps you get comfortable applying what you learn instead of just reading through concepts.
Expert-Led Training: Learn from trainers who have worked in data science and understand how things are done in real projects.
Industry-Standard Tools & Technologies: Use tools like Python, SQL, Pandas, and machine learning libraries that are commonly used in data science roles.
Flexible Learning Options: Choose between classroom or online sessions based on your schedule.
Real-World Project Exposure: Work on projects where you analyze data and build models, so you have something to show when applying for jobs.
Career & Placement Support: Get guidance on resumes, interviews, and job applications, so you’re not figuring it out on your own.
Certification & Skill Validation: Receive a course completion certificate along with practical skills you can actually use.

The course is designed to help you move from learning basics to handling real data with more confidence.

Future Scope of Data Science

Growing Industry Demand

More companies are depending on data to make everyday decisions. Because of that, people who can analyze data and build models are in demand across different industries.

Diverse Career Roles

With data science skills, you can explore roles like:

Data Scientist
Machine Learning Engineer
Data Analyst
AI/ML Engineer

These roles are seen in IT, finance, healthcare, e-commerce, and other growing sectors.

Long-Term Career Relevance

Data science is closely connected with areas like AI and automation. As these continue to grow, the need for people who can work with data is likely to stay strong.

Global Career Opportunities

The skills you learn in data science can be used anywhere. Many companies across the world look for people who can work with data, giving you more flexibility in where you work.

Tools covered for Data Science Course

Data Science & Programming Tools

Python – Core programming for data science, used for data analysis, machine learning, and automation
R Programming – Used for statistical analysis and working with data in research-focused use cases

Data Handling & Analysis Libraries

Pandas – Working with structured data, cleaning, and analysis
NumPy – Handling numerical data and performing calculations efficiently

Machine Learning & AI Libraries

Scikit-learn – Building and testing machine learning models
TensorFlow – Used for deep learning and neural network-based models
Keras – Simplified interface for building deep learning models

Data Visualization Tools

Matplotlib – Creating basic charts and visualizations
Seaborn – Making more detailed and visually clear data plots

Database & Querying Technologies

SQL & MySQL – Managing and querying structured data from databases

Big Data & Processing Tools

Apache Spark – Handling large-scale data processing
Hadoop – Working with distributed data storage and processing

Development & Working Environment

Jupyter Notebook – Writing and running code with explanations in one place
Google Colab – Cloud-based environment to run Python code without setup

Version Control & Collaboration

Git & GitHub – Tracking changes and working on projects collaboratively

Data Science Course Syllabus

Download Syllabus

This Data Science course syllabus is designed to build strong practical skills in working with real-world data. Students learn how to code, work with databases, analyze and visualize data, and transform raw information into meaningful insights. Through hands-on projects, they gain practical experience and confidence to apply these skills in real-world scenarios.

Module 1: Core Python Programming

Introduction to Python, its features, and real-world usage
Working with variables, data types, and operators
Control flow: conditions, loops, and error handling
Functions, modules, and reusable coding practices
Object-Oriented Programming (OOP) concepts
File handling and working with data using Python

Module 2: Data Analysis with Pandas & NumPy

Understanding data structures like Series and DataFrames
Data cleaning, handling missing values, and duplicates
Data manipulation: filtering, sorting, grouping, and merging
Working with CSV files and real datasets
NumPy arrays and numerical computations
Basic data visualization and statistical analysis

Module 3: Data Science Fundamentals & Visualization

Introduction to data science concepts and workflows
Exploratory Data Analysis (EDA) techniques
Data visualization using Matplotlib and Seaborn
Creating charts like bar graphs, scatter plots, heatmaps, and more
Understanding patterns and trends in data

Module 4: Machine Learning Concepts & Models

Introduction to machine learning and its types
Working with Scikit-learn for model building
Supervised and unsupervised learning techniques
Algorithms like Linear Regression, Logistic Regression, KNN, Naive Bayes
Decision Trees, Random Forest, and clustering methods
Model evaluation using accuracy, confusion matrix, and other metrics

Module 5: Advanced Machine Learning & Model Optimization

Feature scaling, normalization, and data preprocessing
Model training, testing, and prediction workflows
Performance tuning and improving model accuracy
Understanding how models behave with different datasets

Module 6: Deep Learning & Artificial Intelligence

Introduction to neural networks and deep learning concepts
Understanding ANN, CNN, and RNN models
Activation functions, layers, and optimizers
Working with image and text datasets
Basic implementation of deep learning models

Module 7: Natural Language Processing (NLP)

Text data processing and cleaning techniques
Working with NLTK and SpaCy
Sentiment analysis and text classification
Understanding language patterns and word relationships

Module 8: Computer Vision

Basics of image processing using OpenCV
Working with image data: resizing, cropping, and transformations
Face detection and object recognition basics
Understanding how visual data is analyzed

Module 9: Generative AI & Large Language Models

Introduction to Generative AI and its applications
Understanding LLMs, transformers, and attention mechanisms
Working with tools like OpenAI, HuggingFace, and LangChain
Prompt engineering basics and building simple AI applications

Real-Time Project Practice in Data Science Course

Project 1Loan Approval Prediction

Work with applicant data to understand key factors that affect loan approvals
Build a model to predict whether a loan is likely to be approved or not

Project 2Customer Churn Prediction

Analyze user data to find patterns behind why customers leave a service
Create a model that helps identify customers who might churn

Project 3Movie Rating Prediction

Use user and movie data to understand rating patterns
Build a system that predicts how users might rate a movie

Project 4Stock Price Trend Analysis

Work with historical stock market data to identify trends
Explore basic models to understand how price movements are analyzed

SLA is a Cetriport Authorised Training & Certification Partner for:

SLA is an authorized certification partner for Microsoft

SLA is an authorized certification partner for PMI

SLA is an authorized certification partner for CSB

Certifications SLA Provides

Our training programs are designed to provide structured learning, practical exposure, and certification support. Students receive multiple certifications based on course participation and completion.

Course Completion Certificate (SLA Institute)
Students who successfully complete the course receive a Course Completion Certificate from SLA Institute, validating their training, skill development, and project work.
Global Certification Preparation & Support
Our curriculum is aligned to support preparation for global certification programs offered by leading organizations such as IBM, Meta, Cisco, HCLTech, and Microsoft.
Students receive guidance and preparation support to pursue relevant certifications based on eligibility and course requirements.
Codeathon Project Certificate
Students who participate in the Codeathon live project program receive a Codeathon Certificate, recognizing their hands-on experience in building end-to-end projects through cross-functional team collaboration.

Certification eligibility, assessments, and issuance are governed by respective organizations and program guidelines.

Placement Support & Career Enablement

Our placement support focuses on helping students become interview-ready and prepared for real job opportunities through continuous guidance and structured career enablement.

What Our Placement Support Covers

Lifelong placement assistance with continuous career guidance
Scheduled interview opportunities through our placement network
Regular campus drives and hiring events
Resume building, profile optimization, and interview preparation
Pre-interview refresh training and post-interview feedback support
Placement tracking through our internal placement management system

Placement support is provided to help students prepare for and participate in interview opportunities. Interview participation and career decisions remain with the student and depend on individual readiness, performance, and available opportunities.

On Average Students Rated The Data Science 4.40/5.0

4.40/5.0

(359)

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Data Science Course with Certification & Placement

No Cost EMI

Have Queries? Ask our Experts

+91 63742 083445

Upcoming Batches

Hands On Training

Real-time projects & assignments

Mock interviews & assessments

Online & classroom learning modes

April 2026

Week days(Mon-Fri)

Online/Offline

April 2026

Week ends(Sat-Sun)

Online/Offline

Save up to 20% in your Course Fee on our Job Seeker Course Series

Quick Enquiry

Placement

Learning

Timings

Mode

Certification

LET US HELP Find Your Perfect Course

We Tie-Up with 1000+ Leading IT and MNC Companies

This Course Includes

Expected Criteria for Assured Placement

Placement Support Guidelines

How Placement Support Works

Have Queries? Ask our Experts

+91 63742 83445

SLA’s Career-Oriented Training & Placement Support Process

1

2

3

4

5

6

Key Features of the Data Science Certification Course

Future Scope of Data Science

Diverse Career Roles

Long-Term Career Relevance

Global Career Opportunities

Achieve Your Goals With SLA

Tools covered for Data Science Course

Data Science & Programming Tools

Data Handling & Analysis Libraries

Machine Learning & AI Libraries

Data Visualization Tools

Database & Querying Technologies

Big Data & Processing Tools

Development & Working Environment

Version Control & Collaboration

Data Science Course Syllabus

Module 1: Core Python Programming

Module 2: Data Analysis with Pandas & NumPy

Module 3: Data Science Fundamentals & Visualization

Module 4: Machine Learning Concepts & Models

Module 5: Advanced Machine Learning & Model Optimization

Module 6: Deep Learning & Artificial Intelligence

Module 7: Natural Language Processing (NLP)

Week days
(Mon-Fri)

Week ends
(Sat-Sun)