Data Science Course with Live Projects & Placement Support – Start2Skill
Job Assistance
For Pro Plan
8 to 9 Month
Duration
Online / Offline
Delivery Mode
English
Language
Beginner to Intermediate
Level
200+ Placed
Live Training
1:1 Mentorship
EMI Available
Everything You Get in This Course
Industry-Focused Projects
- 5+ real-world projects
- Python • Machine Learning • Tableau
- Build job-ready portfolios
- Hands-on problem solving
- Practical exposure to industry scenarios
Career & Placement Support
- Resume & LinkedIn profile building
- Job placement assistance
- Mock interviews & interview prep
- Career guidance from experts
- Opportunities to showcase your skills
Live Instructor-Led Training
- Live interactive sessions
- Weekday & Weekend batches
- Recorded sessions for revision
- 24×7 mentor support
- Doubt-solving & guided learning
Hands-On Learning
- Practical hands-on projects
- Real-world case studies
- Data-driven problem solving
- Industry-relevant assignments
- Learn by doing approach
Certification & Recognition
- Industry-recognized certification
- Proof of skill & course completion
- Shareable digital certificate
- Adds value to your resume
- Valid for career growth
Peer Learning & Networking
- Peer-to-peer learning environment
- Collaborate on projects
- Community discussions & support
- Networking with like-minded learners
- Knowledge sharing sessions
Capstone Project & Mentorship
- Final capstone project
- Apply all learned concepts
- Guided by industry mentors
- Real business problem solving
- Career-focused project experience
Master these Tools
Course Curriculum
1.Preparatory Sessions –Python
Get started with Python through our structured preparatory sessions. Learn the fundamentals, explore essential tools, and gain hands-on experience with guided practice to build a strong programming foundation.
- Introduction to Python and IDEs
- Python Basics
- Hands-on Sessions and Assignments for Practice
2.Data Transformation Using SQL
Master the art of data manipulation with SQL. From foundational concepts to advanced techniques,
explore SQL basics, optimize performance, and dive deep into user-defined functions for efficient data
processing.
- SQL Basics
- Advanced SQL
- Deep Dive into User Defined Functions
3.Python Libraries for Data Science
Harness the power of Python’s top libraries for data science. Learn to handle data with NumPy, manipulate
datasets using Pandas, preprocess data effectively, and create insightful visualizations.
- Data Handling with NumPy
- Data Manipulation Using Pandas
- Data Preprocessing
- Data Visualization
3.Python Libraries for Data Science
Harness the power of Python’s top libraries for data science. Learn to handle data with NumPy, manipulate
datasets using Pandas, preprocess data effectively, and create insightful visualizations.
- Data Handling with NumPy
- Data Manipulation Using Pandas
- Data Preprocessing
- Data Visualization
4.Inferential Analytics
Build a strong foundation in inferential statistics and prescriptive analytics. Learn to leverage Python for
descriptive, diagnostic, and predictive statistical analysis to derive meaningful insights from data.
- Statistics and Descriptive Analytics
- Python for Descriptive, Diagnostic, and Inferential Statistics
- Prescriptive Analytics
5.Machine Learning
Explore the core concepts of machine learning, from regression and classification to clustering
techniques. Gain hands-on experience in building predictive models using real-world datasets.
- Introduction to Machine learning
- Regression
- Classification
- Clustering
6.Supervised Learning
Master supervised learning techniques, including regression models, decision trees, random forests,
and support vector machines. Learn to evaluate model performance using classification reports,
confusion matrices, and time series forecasting.
- Linear Regression Machine learning
- Logistic Regression
- Decision Tree
- Random Forest
- Support Vector Machine
- K-Nearest Neighbours
- Time Series Forecasting
- Performance Metrics
- Classification reports
- Confusion matrix
7.Unsupervised Learning
Understand unsupervised learning methods like K-means clustering and dimensionality reduction
techniques such as PCA and LDA. Learn how to uncover hidden patterns in data without labeled outputs
- K-means
- Dimensionality reduction
- Linear Discriminant Analysis
- Principal Component Analysis
8.Advanced Machine Learning Algorithms
Dive deeper into machine learning with advanced techniques like bagging, boosting, and predictive analytics. Explore cognitive science applications to enhance model performance.
- Bagging And Boosting Algorithms
- Other Machine Learning Algorithms
- Predictive Analytics and Machine Learning
- Cognitive Science and Analytics
9.Data Science at Scale with spark
Learn to handle big data efficiently using Apache Spark. Understand RDDs, advanced Spark concepts, and the integration of Spark with Hive for large-scale data processing.
- Introduction to Big Data and Spark
- RDDs
- Advanced Concepts & Spark-Hive
10.Deep Learning Using TensorFlow
Discover the fundamentals of artificial intelligence and deep learning. Explore neural networks and TensorFlow to build and train deep learning models.
- Artificial Intelligence Basics
- Neural Networks
- Deep Learning
11.Natural Language Processing
Unlock the power of NLP with text mining, sentiment analysis, and sequence modeling. Learn to build AI-driven chatbots and recommendation engines.
- Text Mining, Cleaning, and Pre-processing
- Text classification, NLTK, sentiment analysis, etc
- Sentence Structure, Sequence Tagging, Sequence Tasks,
and Language Modelling - AI Chatbots and Recommendations Engine
12.Power BI
Gain expertise in data visualization and analytics using Power BI. Learn DAX, create interactive
dashboards, and perform hands-on exercises to turn raw data into actionable insights.
- Power BI Basics
- DAX
- Data Visualization with Analytics
- Hands-on Exercise
13.MLOps
Understand MLOps principles for deploying and managing machine learning models in production. Learn best practices for automation, monitoring, and scalability.
- Introduction to MLOps
- Deploying Machine Learning Models
14.Data Science Capstone Project
Apply your knowledge to a real-world data science project. Work on an end-to-end problem statement, integrating machine learning, deep learning, and data visualization techniques.
Perfect For Data Science Career Starters
College
Students
Build projects for campus
placements.
Career
Switchers
No coding experience
needed – start from basics.
Working Professionals
Weekend batches so you can
up-skill while working.
Fresh
Graduates
Job‐ready in 8 months with a
strong portfolio.
Why Start2Skill Data Science > Others
Start2Skill
TOPIC 01
Live mentors with 1:1 guidance from 5+ years industry experts
TOPIC 02
Hands-on real projects with practical, job-ready skills
TOPIC 03
Dedicated placement help with structured interview preparation
TOPIC 04
Flexible batches (weekends + online) with job guarantee
VS
Mentorship
Real Projects
Career Support
Flexibility & Assurance
Others
TOPIC 01
Live mentors with 1:1 guidance from 5+ years industry experts
TOPIC 02
Recorded videos with limited or no real-world projects
TOPIC 03
Generic resume templates, no placement support
TOPIC 04
Fixed schedules with no job guarantee
Meet Your Experts Instructors
Ashutosh Sharma
Rishu Raj Verma
Bhawana aggarwal
Get certified by Start2Skill
Earn industry-backed
Recognition and Career Opportunities
Industry-Endorsed Certificate
Get certified upon course completion with a recognized
credential, validating your skills in Data Science andBusiness Intelligence.
Strong Peer Network
Become part of a thriving community of learners and
professionals from top companies.
Recognized Across Industries
Our certification is trusted by hiring managers across
domains—ideal for career switchers and freshers alike.
What Student Say
How You'll Learn" 4-Step Journey
Talk to a Program
Advisor
Book a free 1:1 counselling call
Enroll in the Right
Course
Get a plan matched to your goals & level.
Learn with Live + Hands-on Projects
Attend live classes and build r
Get Career Guidance & Placement Support
Resume, interviews & job referrals.
Frequently Asked Questions
Who are these courses for?”
These courses are designed for:
Students and freshers who want job-ready skills
Working professionals looking to upskill or switch careers
Freelancers who want to offer services confidently
Business owners who want to understand and manage digital work
No prior experience is required for beginner tracks—advanced tracks may expect basic familiarity.
Do you provide placement support?
Yes, we provide placement support such as:
Resume + portfolio review
Interview preparation (mock interviews + common questions)
Job/internship guidance and referral support (where available)
LinkedIn profile optimization
Note: Placement depends on your performance, attendance, project quality, and market conditions. We support you through the process, but we don’t guarantee jobs.
What is the duration and schedule?
Duration and schedule vary by course, but typically:
Course duration: 4–12 weeks (depending on course level)
Class frequency: 3–5 sessions per week
Session length: 60–120 minutes per class
Weekend batches: Available for working professionals
After enrollment, you’ll receive the full batch calendar and timeline.
Are classes online or offline?
We offer online classes (live instructor-led) and offline classes (at our center), depending on your chosen batch and location.
Some courses may also be available in hybrid mode (offline + recorded support).