Master in Data Science Course
The Data Science Course from SMEClabs will equip you with the essential skills to become a proficient IT professional, mastering the art of data collection, analysis, and evaluation using powerful algorithms. Data science is integral to decision-making in various industries, from banking and healthcare to gaming and augmented reality. With Python, renowned for its open-source nature and libraries like Pandas, NumPy, and SciPy, you’ll learn to navigate and manipulate data to drive successful outcomes. SMEClabs ensures you gain the expertise needed to thrive in this fast-growing sector.


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SMEClabs offers the best training programs with 100% job placement assistance across various fields. Get trained by industry experts, earn certification from recognized bodies, and kickstart your career. Gain hands-on experience with real-world projects and develop the skills needed for a successful career. With SMEClabs, benefit from personalized guidance and support throughout your learning journey.
What Is Data Science Course?
The Advanced Excel Course is designed to provide in-depth knowledge of Microsoft Excel, focusing on its advanced features and tools. This course covers topics such as data analysis, advanced formulas, pivot tables, conditional formatting, data visualization, macros, and automation techniques. It equips learners with the skills to handle complex data, generate insightful reports, and streamline workflows. At SMEClabs, the Advanced Excel Course offers hands-on training to help individuals and professionals become proficient in Excel for enhanced productivity and career growth.
What You Will Learn in the Data Science Course?
In the Advanced Excel Course at SMEClabs, you will learn to harness the full potential of Microsoft Excel for professional use. The course covers advanced formulas, data analysis tools, and visualization techniques to manage and interpret data effectively. You’ll master the use of pivot tables, charts, and conditional formatting to create meaningful reports. Additionally, the course includes automation with macros, VBA scripting, and tips to optimize workflows. With SMEClabs’ hands-on training approach, you’ll gain practical skills to excel in data-driven decision-making and improve your workplace efficiency.
Building Strong Foundations for Professional Success
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International & National Level Certification.
Online Data Science Course
Start instantly and learn at your own schedule, Data Science Course, Quick to become a professional.
Classroom Data Science Course
Get Data Science Course in Classroom at limited locations: Alappuzha, Ernakulam, Idukki, Kannur, Kasaragod, Kerala, Kollam, Kottayam, Kozhikode, Malappuram, Palakkad, Pathanamthitta, Thrissur, Kochi, Wayanad, Chennai, Trivandrum, Mumbai, Calicut, Bangalore, Mangalore, Vizag, Dubai, Saudi Arabia, Qatar, Oman, Kuwait, Nigeria.
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Subscription for remote lab connectivity. 24x7
Flexible Schedule
Set and maintain flexible deadlines.
Data Science Course Overview
Data Science Course - Syllabus
Learn Python Program from Scratch
- Course Introduction
- Programming
Statistical and Mathematical Essential for Data Science
- Introduction
- Sample or Population Data?
- The Fundamentals of Descriptive Statistics
- Measures of Central Tendency, Asymmetry, and Variability
- Practical Example: Descriptive Statistics
- Distributions
- Estimators and Estimates
- Confidence Intervals Lesson
- Practical Example: Inferential Statistics
- Hypothesis Testing: Introduction
- Practical Example: Hypothesis Testing
- The Fundamentals of Regression Analysis
- Assumptions for Linear Regression Analysis
- Dealing with Categorical Data
- Practical Example: Regression Analysis
Data Science with Python
- Python Basics
- Python Data Structures
- Python Programming Fundamentals
- Working with Data in Python
- Data Science Overview
- Data Analytics Overview
- Statistical Analysis and Business Applications
- Python Environment Setup and Essentials
- Mathematical Computing with Python (NumPy)
- Data Manipulation with Pandas
- Machine Learning with Scikit–Learn
- Natural Language Processing with Scikit Learn
- Data Visualization in Python using Matplotlib
- Web Scraping with Beautiful Soup
- Working with NumPy Arrays
Machine Learning
- Introduction to Artificial Intelligence and Machine Learning
- Data Wrangling and Manipulation
- Supervised Learning
- Feature Engineering
- Supervised Learning Classification
- Unsupervised Learning
- Time Series Modeling
- Ensemble Learning
- Recommender Systems
- Text Mining
AI (Natural Language Processing)
- Introduction to Artificial Intelligence and Machine Learning in NLP
- Perform various Text Analysis, Summarization and Extraction, Sentiment Mining, Text Classification, Text Summarization, Information Extraction etc.
- Create a basic speech recognizer to convert speech to text
- Perform advanced Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition
- Implement emotion recognition/sentiment analysis etc. using real time speech recognitions.
Database
- Introduction to SQL
- Database Normalization and Entity-Relationship (ER) Mode
- Installation configurations to setup MySQL
- Understanding Database and Tables
- Learn Operators, Constraints, and Data Types
- Understanding functions, Subqueries, Operators, and Derived Tables in SQL
Flask Web Development
- Routing: Flask’s routing system maps URLs to Python functions, allowing you to define your application’s URL structure.
- Templates: Flask uses Jinja2 as its template engine, allowing you to easily generate dynamic HTML pages.
- Forms: Flask’s form handling makes it easy to process user input and validate data.
- Sessions and cookies: Flask’s session and cookie management features allow you to store user data and maintain state across multiple requests.
- Database integration: Flask can be used with a variety of databases, including MySQL
- RESTful APIs: Flask is a popular choice for building RESTful APIs due to its simplicity and flexibility.
- Extensions: Flask has a wide range of extensions available for adding functionality to your application, including Flask-WTF, Flask-Security, and Flask-Mail.
- Flask-Login: Flask-Login is an extension for handling user authentication and authorization in Flask applications.
- Flask-RESTful: Flask-RESTful is an extension for building RESTful APIs with Flask, providing additional features for API development.
- Deployment: Flask can be deployed to a variety of environments, including traditional web hosting, cloud-based services, and containers.
Fast Api
- Construct Python Micro services with FastAPI
- Understanding FastAPI and Uvicorn
- Installation and Creating Your First API
- Path Parameters
- Query Parameters
- Combining Path and
- Query Parameters
- Query parameter and string
- Path parameter and numeric validation
- Body multiple parameters, body field, body nested models
- Declare request example data
- Cookie parameters
- Response status codes
- Handling errors
- JSON compatible encoder, security
- Bigger applications – multiple files
- Testing and debugging
Django Web Development
- Models: Django’s object-relational mapping (ORM) tool is used to define models, which are Python classes that represent database tables.
- Views: Views are Python functions that handle HTTP requests and return HTTP responses.
- Templates: Django’s template system allows you to define the structure and layout of your web pages.
- Forms: Django provides a powerful form handling system, which makes it easy to process user input and validate data.
- Admin site: Django comes with a built-in admin site, which provides an easy-to-use interface for managing your application’s data.
- Authentication: Django provides built-in authentication mechanisms to handle user authentication and authorization.
- Middleware: Middleware is a mechanism in Django that allows you to process requests and responses before they are handled by views.
- URLs: Django’s URL routing system allows you to map URLs to views and organize your application’s URLs.
- Testing: Django provides a built-in testing framework that makes it easy to write tests for your application.
- Deployment: Django can be deployed to a variety of environments, including traditional web hosting, cloud-based services, and containers.
Big Data Analytics
- Introduction to Hadoop, Architecture, Administration and Components
- Understanding NoSQL Databases HBase
- Understand basic object-oriented programming methodologies in Scala
- Introduction to Scala, Basics of Functional Programming, Case Objects and Classes Collections
- Introduction to Spark, Work with RDD in Apache Spark, processing real time data
- Perform DataFrame operations in Spark using SQL queries
- Spark MLib Modelling Big Data with Spark
- Introduction to Spark GraphX
AI, Deep Learning, Computer vision (OpenCV)
- Introduction to Hadoop, Architecture, Administration and Components
- Understanding NoSQL Databases HBase
- Understand basic object-oriented programming methodologies in Scala
- Introduction to Scala, Basics of Functional Programming, Case Objects and Classes Collections
- Introduction to Spark, Work with RDD in Apache Spark, processing real time data
- Perform DataFrame operations in Spark using SQL queries
- Spark MLib Modelling Big Data with Spark
- Introduction to Spark GraphX
Kafka, MQTT and AWS IOT
- Understanding Data Science IOT data pipelines
- Understanding MQTT and Kafka to build IOT systems
- Configuring MQTT
- Understand MQTT subscriber, publisher and brokers
- Deploying HIVE MQTT services with IOT device
- Understanding AWS IOT core
- Configuring and managing AWS services
- Deploy IoT devices with AWS IoT Core, AWS IoT Device
- Management, and AWS IoT
Analytics
Job Opportunities After Completing Data Science Course
- Data Scientist/Analyst - Machine Learning/Deep Learning
- Artificial Intelligence Expert - Data Scientist/ Machine Learning
- Data Engineer
- Research Engineer - Data Analytics & Artificial Intelligence
Who Should Attend the Data Science Course
- Ideal for those passionate about analyzing data and solving complex challenges.
- Suitable for freshers, as the course starts from the basics and gradually builds advanced skills.
- Perfect for software engineers, analysts, and professionals looking to transition into data science.
- Developers aspiring to become data scientists will find the course a great fit.
- Analytics managers can enhance their leadership and analytical skills.
- Business analysts will gain a deeper understanding of machine learning techniques.
- Information architects will gain expertise in predictive analytics.
- R professionals looking to work with big data will benefit from specialized training.
- Designed to help participants master data science methodologies and apply them in real-world scenarios.
Data Science Course offered by SMEClabs
Difficulty – Beginner / No experience | Eligibility – Any Degree, Diploma, Graduates | Mode – Offline – 240 Hours / OnDemand / Hybrid
Detailed Syllabus | Enroll Now
SMEClabs’ Master in Data Science course provides downloadable datasets and solutions, allowing you to practice alongside the video tutorials. The course also includes quick reference guides for each lesson to reinforce your knowledge and ensure a comprehensive understanding of data science concepts.
Why Choose a Career in Data Science?
- The demand for Data Science and Analytics professionals is skyrocketing, with nearly 364,000 new job listings projected by 2020, according to Forbes.
- Data scientists earn an impressive average salary of $120k, as reported by Glassdoor.
- Businesses leveraging data analytics are expected to see $430 billion in productivity benefits over their competitors who don't use data analysis, by 2020.
Key Features
- Offline/Online Classes
- Case Studies and Assignments
- Hands-on Projects
- Mentoring Sessions
- Job Assistance
Data Science Course – Training at SMEClabs
SMEClabs’ Data Science Course offers comprehensive training to help you build expertise in this rapidly growing field. With flexible offline/online classes, you can choose a learning format that fits your schedule. The course includes real-world case studies, assignments, and hands-on projects that allow you to apply concepts and build a strong portfolio. Personalized mentoring sessions from industry experts provide valuable guidance, while our job assistance helps you secure a career in data science. Whether you’re starting from scratch or advancing your skills, SMEClabs equips you with the knowledge and tools needed to succeed in the data science industry.
Achieve a Rewarding Career as a Data Science Expert with SMEClabs
Embark on a journey to becoming a skilled Data Science professional with SMEClabs. Our comprehensive training program is designed to equip you with the knowledge and hands-on experience needed to excel in this high-demand field. With flexible offline/online classes, practical case studies and assignments, real-world projects, and personalized mentoring sessions, you will gain the expertise required to analyze data and make impactful decisions. Plus, our job assistance ensures you have the support needed to secure a rewarding career in Data Science. Start your path to success with SMEClabs and unlock your future as a Data Science expert.
Why Choose SMEClabs?
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Data Science Course: FAQ
Which course is better for a career in Data Science?
Master in Data Science: This is an advanced program that provides in-depth knowledge and covers a wide range of topics. It’s ideal for those looking to build a strong academic foundation and advance in the field.
Data Scientist in Python: This course focuses specifically on Python, which is the most widely used programming language in data science. If you’re aiming to specialize in Python for data analysis and machine learning, this could be a great choice.
IBM Data Science Certification: An industry-recognized certification from IBM, this course covers various tools and techniques used in data science and is suitable for those who want a structured, practical learning path.
Data Science for Business: This course is ideal if you want to focus on applying data science skills specifically in a business context, such as making data-driven decisions and optimizing business processes.
Is Data Science a good paying job?
Yes, data science is one of the highest-paying fields. In India, the salary for a data scientist ranges from ₹2 lakh to ₹20 lakh, with an average salary of ₹9 lakh per year.
Is Data Science a good career choice in 2023?
Yes, data science is a highly promising career choice in 2023. Most organizations are leveraging data science for business decisions, operational improvements, and innovation. Data is crucial across industries for making data-driven decisions, ensuring job stability and growth potential in this field.
What are the major skills required for a Data Scientist?
To become a successful data scientist, you should have skills in:
- Deep Learning
- Mathematics (especially statistics)
- Machine Learning
- Programming (primarily in Python)
- Data Processing and Data Analysis
Is AI a threat to Data Science?
While AI can automate certain tasks in data science, it is unlikely to replace data scientists entirely. AI tools can help streamline and optimize processes, but data scientists will continue to play a crucial role in interpreting data, designing models, and making critical business decisions.
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