Data Science Certification Course | Professional Data Science Training
Advance your career with our Data Science Certification Course. This Data Science Online Course offers hands-on Data Science Training, real-world projects, and expert guidance to help you earn a recognized Certification in Data Science.
- Industry Expert Trainers
- Online learning session
- Accredited Trainer
- Exam fee included
Certified Data Science Professional Course Overview
The Data Science Course is designed to help you build a strong foundation in data analysis, machine learning, and statistical modeling while focusing on real-world applications. This Data Science Certification Course covers essential concepts such as data wrangling, visualization, predictive analytics, and AI-driven decision-making, enabling you to turn raw data into meaningful insights.
Through this Data Science Online Course, you will gain hands-on experience with tools and technologies like Python, R, SQL, and big data frameworks. The course also introduces key areas such as data extraction, machine learning algorithms, and data visualization techniques, helping you understand how data science is applied across industries.
With Data Science Training from NovelVista, you will not only learn theoretical concepts but also apply them through practical exercises, case studies, and simulations. The program is structured to prepare you for real-world challenges, making it suitable for aspiring data scientists, analysts, and professionals looking to transition into data-driven roles.
Earning this Data Science Professional Certification validates your ability to handle complex datasets, build predictive models, and support business decisions with data. It also enhances your career prospects by positioning you as a skilled and industry-ready data professional.
What You Will Get?
Learning Outcome
After the completion of the course, the participants would be able to:
Training Calendar
English
- Self paced videos, assessments, recall quizzes, more
- For more details, reach us at training@novelvista.com
Includes Training, Exam & Certification
Lifetime Access
- Self paced videos, assessments, recall quizzes, more
- For more details, reach us at training@novelvista.com
Includes Training, Exam & Certification
Course Curriculum
Before you begin, this Data Science Online Course is structured to build your skills step-by-step, from fundamentals to advanced techniques. The curriculum focuses on practical learning, helping you apply data science concepts in real-world scenarios.
1. Introduction to Data Science+
This module introduces the fundamentals of data science, its importance, and how it is applied across industries to solve real-world problems using data-driven approaches.
- Data Science Overview: Understand what data science is, its importance, and how it helps organizations make informed decisions using data.
- Key Concepts & Terminology: Learn essential data science terms and concepts required to build a strong foundational understanding.
- Data Science Lifecycle: Explore stages like data collection, preparation, analysis, and interpretation in a structured workflow.
- Tools & Technologies: Get introduced to tools like Python, R, SQL, and their role in data science projects.
- Data Science Roles: Understand different roles, such as data scientist, analyst, and engineer, and their responsibilities.
2. Probability & Statistics+
This module builds a strong statistical foundation required for data analysis and machine learning.
- Probability Concepts: Learn basic probability theory, random variables, and probability distributions.
- Statistical Methods: Understand descriptive and inferential statistics for analyzing data effectively.
- Regression & Correlation: Explore relationships between variables using correlation and regression techniques.
- Hypothesis Testing: Learn how to validate assumptions and make data-driven conclusions.
- Bayesian Statistics: Understand Bayesian approaches for probabilistic analysis and decision-making.
3. Working with Big Data+
This module focuses on handling large datasets using modern big data technologies and frameworks.
- Big Data Fundamentals: Understand what big data is, its characteristics, and challenges in processing large datasets.
- Big Data Technologies: Learn about tools like Hadoop, Spark, and NoSQL databases.
- Data Storage Solutions: Explore storage systems such as HDFS, Cassandra, and MongoDB.
- Processing Frameworks: Understand frameworks like MapReduce and Spark for data processing.
- Real-World Applications: Learn how big data is used across industries for decision-making.
4. Data Extraction & Visualization+
This module covers techniques to collect, clean, and visualize data effectively.
- Data Extraction Methods: Learn techniques like web scraping, APIs, and database queries for data collection.
- Data Cleaning & Preparation: Understand how to handle missing values and transform data for analysis.
- Visualization Basics: Learn principles and the importance of data visualization.
- Visualization Techniques: Explore charts, graphs, and dashboards for presenting insights.
- Visualization Tools: Get introduced to tools like Matplotlib, Seaborn, and Plotly.
5. Data Mining & Machine Learning+
This module introduces core machine learning concepts and techniques used to extract insights and build predictive models from data.
- Data Mining Concepts: Understand key concepts and techniques used to discover patterns and insights from large datasets.
- Machine Learning Types: Learn supervised, unsupervised, and reinforcement learning approaches used in data science.
- Key Algorithms: Explore algorithms like regression, classification, clustering, and association techniques.
- Model Evaluation: Learn methods to evaluate and validate machine learning model performance.
- Real-World Applications: Understand how machine learning is applied to solve practical business problems.
6. Statistical Methods for Data Science+
This module focuses on advanced statistical techniques used for deeper data analysis and modeling.
- Advanced Statistics: Learn multivariate analysis, time series analysis, and survival analysis techniques.
- Statistical Inference: Understand estimation, confidence intervals, and significance testing.
- Experimental Design: Learn how to design experiments and analyze results effectively.
- Statistical Tools: Work with tools like R and Python libraries for statistical analysis.
- Practical Applications: Apply statistical methods to solve real-world data science problems.
7. Text Mining & NLP+
This module introduces techniques for analyzing and extracting insights from textual data.
- Text Mining Basics: Understand techniques and challenges involved in processing text data.
- NLP Fundamentals: Learn preprocessing methods like tokenization, stemming, and lemmatization.
- Text Analysis Techniques: Explore classification, sentiment analysis, and topic modeling methods.
- Advanced NLP: Understand concepts like word embeddings, transformers, and modern NLP models.
- NLP Tools: Work with tools like NLTK, SpaCy, and Gensim.
8. Data Visualization with Tableau+
This module focuses on advanced data visualization and storytelling using Tableau.
- Tableau Introduction: Learn the basics of Tableau, installation, and connecting to data sources.
- Basic Visualizations: Create charts like bar graphs, line charts, and pie charts.
- Advanced Visualizations: Explore heat maps, scatter plots, and complex visualizations.
- Dashboards & Storytelling: Build interactive dashboards and present insights effectively.
- Advanced Tableau Features: Learn data manipulation, calculations, and integration with other tools.
Course Details
What Will You Get?+
By enrolling in this Data Science Certification Course, you gain practical tools, structured learning, and industry-relevant resources to build strong data science expertise:
- Comprehensive Data Science Online Training with structured, easy-to-follow modules
- Hands-on experience with real-world data analysis and machine learning techniques
- Access to engaging video lessons and expert-led learning content
- AI-based roleplay and simulations for practical understanding
- Downloadable resources, templates, and reference materials
- Mock exams with multiple attempts for effective exam preparation
- Certification exam voucher with defined validity
- Two exam attempts for the Data Science Certification
- Globally recognized Data Science Professional Certification validating your skills
- Lifetime validity of certification with continuous professional value
Eligibility+
The Data Science Certification Course is suitable for individuals looking to build or advance their skills in data analysis, machine learning, and data-driven decision-making.
- Students and freshers interested in starting a career in data science
- Professionals looking to transition into data-driven roles
- Data analysts, business analysts, and IT professionals
- Anyone interested in Data Science Training and analytics
- Individuals aiming to earn a Data Science Professional Certification
This Data Science Online Course is designed for both beginners and experienced professionals who want to develop practical data science skills.
Prerequisites+
There are no strict prerequisites for enrolling in this Data Science Online Course. However, having the following knowledge will help you learn more effectively:
- Basic understanding of mathematics and statistics
- Familiarity with programming concepts (Python preferred, but not mandatory)
- Interest in data analysis and problem-solving
- Awareness of business processes or analytical thinking (helpful)
This Data Science Training is designed to support both beginners and professionals, helping you build practical skills from the ground up.
Training Delivery Style+
This Data Science Online Course is delivered in a self-paced learning format, allowing you to learn anytime, anywhere, based on your schedule.
Key features of the delivery include:
- Self-paced access to structured Data Science Training modules
- Engaging video lessons with real-world examples and case studies
- AI-based roleplay and simulations for practical learning
- Access to mock exams for effective exam preparation
- Downloadable resources and reference materials
- Flexible access for continuous learning and skill development
This format ensures you can build practical data science skills at your own pace while preparing for your Data Science Professional Certification.
Key Benefits of the Data Science Course+
- Practical Data Skills – Learn to analyze, interpret, and work with real-world data to solve business problems effectively.
- End-to-End Learning – Gain a complete understanding of the data science lifecycle from data collection to model deployment.
- Hands-On Experience – Apply concepts through practical exercises, projects, and real-world scenarios.
- Machine Learning Expertise – Build and evaluate models using core machine learning algorithms and techniques.
- Data Visualization Skills – Create clear and impactful visualizations to communicate insights effectively.
- Tool Proficiency – Work with tools like Python, R, SQL, and big data technologies used in industry.
- Career Growth – Enhance your profile for roles in data science, analytics, and AI-driven domains.
- Globally Recognized Certification – Earn a Data Science Professional Certification that validates your expertise.
- Industry-Relevant Knowledge – Stay updated with current data science trends, tools, and methodologies.
- Future-Ready Skillset – Build in-demand skills required for data-driven decision-making across industries.
Certified Data Science Professional Exam Format
Exam Format - Objective Type, Multiple Choice
Exam Duration - 1 Hour
No. of Questions - 40 (multiple-choice questions)
Passing Criteria - 26 out of 40 (65%)
Certificate - Within 5 business days
Result - Immediately after the exam
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