Data Science
Top-Rated Data Science Course Online for Beginners Today
Learning Objectives
- Understand fundamental concepts of data science and its applications.
- Explain the importance of data in decision-making processes.
- Apply mathematical and statistical methods to analyze data.
- Utilize Excel and Power BI for data visualization and analysis.
- Implement Python programming for data manipulation and machine learning.
- Analyze datasets to derive meaningful insights and conclusions.
- Evaluate the performance of machine learning models.
- Create and present data-driven reports and visualizations.
- Develop and enhance problem-solving and critical-thinking skills.
Course Duration
Total
Duration
12 Weeks (3 Months)
3 Weeks Placement Readiness
Weekly
Commitment
10-12 Hours
Pre-Requisites
Basic Computer Literacy
Familiarity with operating systems, file management, and basic software installation.
Mathematics Basics
Understanding of high school-level mathematics.
Basic Programming Knowledge (Preferred)
Familiarity with any programming language (preferable but not mandatory).
Course Outline
Introduction to Data Science
Day 1: Overview of Data Science (Live Class, 90 mins)
- Video: Introduction to Data Science
- Reading Material: Overview of Data Science
- Quiz: Basics of Data Science
Day 2: Data Collection Methods (Live Class, 90 mins)
- Reading Material: Data Sources and Collection
- Practical Assignment: Collecting Data from APIs
Day 3: Data Cleaning and Preprocessing (Live Class, 90 mins)
- Video: Data Cleaning Techniques
- Practical Assignment: Cleaning a Dataset in Excel
Day 4: Introduction to Python for Data Science (Live Class, 90 mins)
- Reading Material: Python Basics
- Practical Assignment: Writing Basic Python Scripts
Day 5: Data Types and Data Structures in Python (Live Class, 90 mins)
- Video: Python Data Structures
- Quiz: Python Basics
Excel for Data Analysis
Day 1: Excel Basics for Data Analysis (Live Class, 90 mins)
- Reading Material: Excel Fundamentals
- Practical Assignment: Basic Excel Functions
Day 2: Data Cleaning in Excel (Live Class, 90 mins)
- Video: Excel Data Cleaning Techniques
- Practical Assignment: Cleaning a Dataset in Excel
Day 3: Data Analysis with Excel (Live Class, 90 mins)
- Reading Material: Excel Data Analysis Tools
- Practical Assignment: Analyzing a Dataset in Excel
Day 4: Advanced Excel Functions (Live Class, 90 mins)
- Video: Advanced Excel Techniques
- Quiz: Excel Functions
Day 5: Excel Dashboarding (Live Class, 90 mins)
- Reading Material: Creating Dashboards in Excel
- Practical Assignment: Building an Excel Dashboard
Data Visualization with power BI
Day 1: Introduction to Power BI (Live Class, 90 mins)
- Video: Getting Started with Power BI
- Reading Material: Power BI Basics
Day 2: Connecting and Transforming Data in Power BI (Live Class, 90 mins)
- Practical Assignment: Data Connections in Power BI
Day 3: Creating Visualizations in Power BI (Live Class, 90 mins)
- Video: Visualization Techniques in Power BI
- Practical Assignment: Building Power BI Reports
Day 4: Advanced Power BI Features (Live Class, 90 mins)
- Reading Material: Advanced Power BI
- Quiz: Power BI Features
Day 5: Power BI Dashboards (Live Class, 90 mins)
- Practical Assignment: Creating Interactive Dashboards in Power BI
Data Analysis with Python
Day 1: Introduction to Pandas (Live Class, 90 mins)
- Video: Getting Started with Pandas
- Reading Material: Pandas Basics
Day 2: Data Cleaning with Pandas (Live Class, 90 mins)
- Practical Assignment: Cleaning Data with Pandas
Day 3: Data Manipulation with Pandas (Live Class, 90 mins)
- Reading Material: Advanced Pandas
- Practical Assignment: Data Transformation with Pandas
Day 4: Data Analysis with Pandas (Live Class, 90 mins)
- Video: Analyzing Data with Pandas
- Practical Assignment: Performing EDA with Pandas
Day 5: Data Visualization with Matplotlib (Live Class, 90 mins)
- Practical Assignment: Creating Plots with Matplotlib
Statistics for Data Science
Day 1: Introduction to Statistics (Live Class, 90 mins)
- Reading Material: Basic Statistical Concepts
- Quiz: Basic Statistics
Day 2: Descriptive Statistics (Live Class, 90 mins)
- Video: Descriptive Statistics Techniques
- Practical Assignment: Descriptive Analysis in Python
Day 3: Inferential Statistics (Live Class, 90 mins)
- Reading Material: Inferential Statistics Concepts
- Practical Assignment: Hypothesis Testing in Python
Day 4: Probability Theory (Live Class, 90 mins)
- Video: Introduction to Probability
- Quiz: Probability Concepts
Day 5: Statistics with Python (Live Class, 90 mins)
- Practical Assignment: Statistical Analysis with Python
Exploratory Data Analysis (EDA)
Day 1: EDA Overview (Live Class, 90 mins)
- Video: EDA Techniques
- Reading Material: Importance of EDA
Day 2: Data Visualization for EDA (Live Class, 90 mins)
- Practical Assignment: Visualizing Data for EDA
Day 3: Summary Statistics and Data Distributions (Live Class, 90 mins)
- Reading Material: Data Distributions
- Practical Assignment: Calculating Summary Statistics
Day 4: Identifying Patterns and Outliers (Live Class, 90 mins)
- Video: Detecting Outliers
- Practical Assignment: Analyzing Patterns in Data
Day 5: EDA Project (Live Class, 90 mins)
- Practical Assignment: EDA on a Real Dataset
Introduction to Machine Learning
Day 1: Machine Learning Basics (Live Class, 90 mins)
- Reading Material: Introduction to Machine Learning
- Quiz: Machine Learning Concepts
Day 2: Supervised Learning – Regression (Live Class, 90 mins)
- Practical Assignment: Implementing Linear Regression
Day 3: Supervised Learning – Classification (Live Class, 90 mins)
- Video: Classification Techniques
- Practical Assignment: Implementing Logistic Regression
Day 4: Unsupervised Learning – Clustering (Live Class, 90 mins)
- Practical Assignment: Implementing K-Means Clustering
Day 5: Model Evaluation and Validation (Live Class, 90 mins)
- Reading Material: Model Evaluation Techniques
- Quiz: Model Evaluation
Advanced Machine Learning
Day 1: Decision Trees and Random Forests (Live Class, 90 mins)
- Video: Tree-Based Methods
- Practical Assignment: Implementing Decision Trees
Day 2: Ensemble Methods (Live Class, 90 mins)
- Reading Material: Ensemble Techniques
- Practical Assignment: Implementing Random Forests
Day 3: Support Vector Machines (Live Class, 90 mins)
- Practical Assignment: Implementing SVM
Day 4: Neural Networks Introduction (Live Class, 90 mins)
- Video: Basics of Neural Networks
- Quiz: Neural Networks Concepts
Day 5: Model Tuning and Optimization (Live Class, 90 mins)
- Practical Assignment: Hyperparameter Tuning
Big Data Technologies
Day 1: Introduction to Big Data (Live Class, 90 mins)
- Reading Material: Big Data Concepts
- Quiz: Big Data Basics
Day 2: Working with Hadoop (Live Class, 90 mins)
- Video: Hadoop Ecosystem
- Practical Assignment: Introduction to Hadoop
Day 3: Introduction to Spark (Live Class, 90 mins)
- Practical Assignment: Working with Spark
Day 4: SQL for Data Science (Live Class, 90 mins)
- Reading Material: SQL Basics
- Practical Assignment: Writing SQL Queries
Day 5: Integrating Big Data Tools (Live Class, 90 mins)
- Practical Assignment: Big Data Project
Real-World Data Science Applications
Day 1: Case Studies in Data Science (Live Class, 90 mins)
- Video: Successful Data Science Projects
- Reading Material: Data Science Case Studies
Day 2: Industry-Specific Data Science Applications (Live Class, 90 mins)
- Practical Assignment: Analyzing Industry Data
Day 3: Ethics in Data Science (Live Class, 90 mins)
- Reading Material: Data Ethics
- Quiz: Ethical Considerations in Data Science
Day 4: Data Science for Social Good (Live Class, 90 mins)
- Practical Assignment: Social Good Project
Day 5: Capstone Project Planning (Live Class, 90 mins)
- Practical Assignment: Project Proposal
Capstone Project Development
Day 1: Project Development – Data Collection (Live Class, 90 mins)
- Practical Assignment: Collecting Project Data
Day 2: Project Development – Data Cleaning (Live Class, 90 mins)
- Practical Assignment: Cleaning Project Data
Day 3: Project Development – Data Analysis (Live Class, 90 mins)
- Practical Assignment: Analyzing Project Data
Day 4: Project Development – Visualization (Live Class, 90 mins)
- Practical Assignment: Visualizing Project Data
Day 5: Project Development – Modeling (Live Class, 90 mins)
- Practical Assignment: Building Project Models
Capstone Project and Review
Day 1: Finalizing Capstone Project (Live Class, 90 mins)
- Practical Assignment: Finalizing Project Report
Day 2: Preparing for Presentation (Live Class, 90 mins)
- Practical Assignment: Creating Presentation Slides
Day 3: Presentation Skills Workshop (Live Class, 90 mins)
- Video: Effective Presentation Techniques
- Practical Assignment: Practicing Presentation
Day 4: Capstone Project Presentation (Live Class, 90 mins)
- Practical Assignment: Presenting Capstone Project
Day 5: Review and Feedback (Live Class, 90 mins)
- Practical Assignment: Incorporating Feedback
- Reading Material: Reflective Analysis
Course Outline Chart
Learn from Experts And Get Data Science Certification From Top Industry
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Benefits of Enrolling in data science course in india
High Demand for Data Science Professionals
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Data science roles often offer high-paying job opportunities worldwide
Versatility Across Industries
Data science expertise is crucial in sectors like finance, healthcare, and e-commerce.
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It’s your ticket to mastering Python, SQL, and real-world analytics—guided by industry mentors, built for real career results
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Learning data science opens doors to high-demand careers in tech, finance, healthcare, and more.It equips you with skills to analyze data, build models, and make smarter business decisions. Explore the online data science course with placement to get started with practical, career-focused training.
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Future-Proof Your Career The demand for data-savvy professionals is booming across industries. A data science course online equips you with the skills needed to thrive in today’s digital job market.
Gain Practical, In-Demand Skills From Python to machine learning, data science teaches you tools that drive real impact. The best data science courses focus on hands-on learning that prepares you for real-world challenges.
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What Roles Can a Data Science Professional Pursue?
Frequently Asked Questions
Data Science is the art and science of extracting meaning from raw data using tools like Python, Machine Learning, and SQL. With a data science course online, you can learn how to analyze, predict, and drive major business decisions—and kickstart an exciting, future-proof career.
If you're serious about wanting to become a data scientist, the best choice is a hands-on data science course online that offers real-world projects, personalized mentorship, and placement support. Hyperlaunch offers everything you need—flexible learning, industry exposure, and a clear roadmap to get job-ready fast.
Hyperlaunch's online data science course with placement is built to help you skip the guesswork. You get live sessions, career mentorship, resume building, mock interviews, and guaranteed placement assistance. It's designed for anyone serious about landing a data role—not just learning theories.
After completing a data science course near me (or online), you open doors to top roles like Data Scientist, Data Analyst, Machine Learning Engineer, Data Engineer, and Business Intelligence Analyst across industries like finance, healthcare, tech, and e-commerce.
The average salary of a data scientist in India ranges from ₹8L to ₹20L per year, depending on your skills and experience. Completing a strong data science course in Chennai or a trusted platform like Hyperlaunch can fast-track your entry into high-paying roles.
