Data Science
So many MNCs are waiting for you!
We are best certification online/offline program for Data Science
Let Your Successful Career Begin With Us
Access to Job Portal
LMS SUPPORT
FREE LAPTOP
About Program
Data science is a field that involves using statistical methods, algorithms, and tools to extract insights and knowledge from structured and unstructured data. It combines domains such as mathematics, computer science, and subject matter expertise to make data-driven decisions and predictions.
The ultimate goal of data science is to help organizations make informed decisions based on data analysis, leading to better business outcomes. Data scientists leverage techniques such as data mining, machine learning, and artificial intelligence to analyze and interpret data, identify patterns and trends, and create predictive models.
Data science courses cover skills such as data analysis, visualization, machine learning, programming, and data management, making you more marketable to potential employers in various industries.
Data science courses provide you with the skills to
work with large datasets, including data preprocessing, integration, and analysis techniques that can inform data-driven decisions.
Data science courses equip you with
critical thinking, problem-solving, and analytical skills essential for tackling real-world challenges.
Data science courses cover various
machine learning algorithms and techniques, enabling you to build predictive models and implement artificial intelligence solutions.
Data science courses allow you to specialize in specific domains, such as finance, healthcare, or
marketing, gaining industry-specific expertise
Data science courses provide networking
opportunities with professionals, alumni, and peers, expanding your professional network and potentially leading to job opportunities
Why Choose This Course
Explore Best Online Courses
Course Features
LMS support
Our Learning Management System (LMS) support provides access to online resources, including course materials, assignments, and assessments.
Placements
Job placement assistance will include resume building, job search assistance, and networking opportunities with potential employers.
Free Laptop
We offer free laptops to students who enroll in courses. This provides students with the necessary tools to complete their coursework and prepare for job opportunities.
Quality Training
Quality of training provided by us both online and offline will be best. The training will be comprehensive, up-to-date, and delivered by experienced professionals.
Live projects and Tools
We provide you with opportunities to work on real-life projects and use industry-standard tools. It gives students practical experience and prepares you for real-world work environments.
Pre-Placement sessions
This involves preparing you for the job placement process, including resume building, job search strategies, and interview preparation.
One to one interview preparations
We will prepare you for the job placement process, including resume building, job search strategies, and interview preparation.
Internship Program
Internships can be an excellent way to network with professionals in the industry. Individuals can make connections with mentors, colleagues, and potential employers, which can be valuable for future job opportunities.
Aptitude Preparation
Soft skills sessions will have training on skills, such as communication, teamwork, and problem-solving. These skills are important for success in the workplace and are often valued by employers.
Programs We Offer
P.G. Diploma in Data Science
12 Months For Learners With No Coding Experience
Advanced Diploma in Data Science
6 Months For Learners With Basic Coding Experience
Certification in Data Science
3 Months For Learners With Notable Coding Experience
TOOLS
These tools will master you in data science and will enhance your skill set with practical approach
Course Details
12 Months
P.G. Diploma in Data Science
Soft Skill Training Included
2.5 to 3 Hours
- Basics of Statistics
- Introduction to Data Science
- Python Basics
- Data Analysis With Excel and Tableau
- Python Programming
- Advanced Statistics with
- Data Analysis
- Data Wrangling With SQL
- Emerging Trends in Data Science
- Data Structure & Algorithms
- Introduction to R Programming
- Machine Learning With R and Python
- Machine Learning I: Supervised
- Machine Learning II: Unsupervised
Deep Learning: - Neural Networks
- Natural Language Processing
- Computer Vision
- Convolutional Neural Networks (CNNs)
- Recurrent neural networks (RNNs)
6 Months
Advanced Diploma in Data Science
Soft Skill Training Included
1.5 to 2 Hours
- Python Programming
- Advanced Statistics with
- Data Analysis
- Data Wrangling With SQL
- Emerging Trends in Data Science
- Data Structure & Algorithms
- Introduction to R Programming
- Machine Learning With R and Python
- Machine Learning I: Supervised
- Machine Learning II: Unsupervised
Deep Learning: - Neural Networks
- Natural Language Processing
- Computer Vision
- Convolutional Neural Networks (CNNs)
- Recurrent neural networks (RNNs)
3 Months
Certification in Data Science
Soft Skill Training Included
1 to 1.5 Hours
- Data Structure & Algorithms
- Introduction to R Programming
- Machine Learning With R and Python
- Machine Learning I: Supervised
- Machine Learning II: Unsupervised
Deep Learning: - Neural Networks
- Natural Language Processing
- Computer Vision
- Convolutional Neural Networks (CNNs)
- Recurrent neural networks (RNNs)
EDUCATION LOAN | FREE LAPTOP | LMS SUPPORT
Topics Covered
- Introduction to Statistics
- Collection and Scrutiny of Data
- Classification and Tabulation of Data
- Diagrammatic Presentation of Data
- Graphical Presentation of Data
- Measures of Central Tendency (Mean,
- Median and Mode)
- Measures of Dispersion
- Correlation Coefficient
- Rank Correlation
- Intra-Class Correlation
- Basics of Data
- What is Data Science?
- Data Science and Ethical Issues
- Big Data and Data Science Hype,
- Datafication
- Understand Data Science Pipeline
- Getting and Cleaning Data
- Visualizing the Data
- The Data Scientist’s Toolbox
- Applications of Data Science in Business
- Case Study
- Introduction to Python
- Install Python
- Variables, expressions and statements
- Functions
- Conditionals, recursion and iteration
- Strings
- Lists
- Tuples
- Dictionaries
- Object Oriented Programming
- Files and Error Handling
- Testing, Debugging and Profiling
- Data Structures – Linked lists, Stacks,Queues and Trees
- Introduction to Excel and Tableau
- Data Import and Management
- Data Visualization
- Descriptive Statistics
- Pivot Tables
- Data Analysis with Excel Functions
- Advanced Data Visualization
- Calculated Fields and Table Calculations
- Mapping and Geographic Analysis
- Case Studies
- Control Statements
- Data Structures
- NumPy, Pandas, Seaborn
- Matplotlib
- Scikit-learn
- Data Cleaning and Preprocessing
- Web Scraping
- Beautifulsoup
- Data Wrangling
- Object-Oriented Programming
- Multiple Correlation
- Partial Correlation
- Introduction to Probability
- Different Approaches to Probability Theory
- Laws of Probability
- Linear Regression
- Multiple Regression
- Introduction to Sample Surveys
- Simple Random Sampling
- Stratified Random Sampling, Other Sampling Schemes
- Analysis of Variance
- Data sanitization
- Introduction to SQL
- Data Types in SQL
- Function, Filtering
- Subqueries
- SQL Statements
- GROUP BY & Aggregation
- Indexes & Partitioning
- JOINS
- SQL operators
- Big Data
- Apache Spark and Scala
- Deep Learning
- Artificial Intelligence
- Business Intelligence
- Natural Language Processing
- Types of Analytics – Descriptive, Predictive, Prescriptive
- Business Analytics
- Web Analytics
- Next-generation data analytics
- Case Study
- Programming Fundamentals
- Data types
- Arrays and Pointers
- Functions
- Stack and Queues
- Linked List
- Trees
- Searching Algorithms
- Sorting Algorithms
- Graphs
- Dynamic Programming
- Data Structures in R
- Install R, RStudio, R Package
- Data Cleaning
- Data Manipulation
- Data Modeling
- Text Mining
- Time Series Analysis
- Web Scraping
- Basic Expressions – Conditional, Loop
- Package Development
- Debugging
- Parallel R and String Manipulation
- Basics of Machine Leaning
- Supervised Machine Learning – K-NN, Naïve Bayes,
- Decision tree, SVM
- Unsupervised Machine Learning – K means, Apriori
- algorithms
- Regression Models
- Clustering Models
- knitr, RPub, R Markdown, swirl, ggplot2
- Computation with Python – NumPy, SciPy
- Data Manipulation in Python- Pandas
- Understanding DataFrame
- Data Visualisation in Python – matplotlib
- Introduction to Scikit – Machine learning
- Web Scraping in Python – BeautifulSoup
- Integration using PySpark, Hadoop, MapReduce
- Convolutional Neural Networks (CNNs)
- Recurrent Neural Networks (RNNs)
- Generative Adversarial Networks (GANs)
- Autoencoders
- Perceptrons
- Multi-Layer Perceptrons (MLPs)
- Backpropagation
- Tensorflow
- Deep Belief Networks (DBNs)
- Long Short-Term Memory (LSTM)
- Self-Organizing Maps (SOMs)
- Text Preprocessing
- Text Classification
- Named Entity Recognition (NER)
- Part-of-Speech (POS) Tagging
- Sentiment Analysis
- Topic Modeling
- Word Embeddings
- Language Modeling
- Machine Translation
- Text Generation
- HuggingFace
- Image Processing
- Image Segmentation
- Object Detection
- Object Recognition
- Facial Recognition
- Pose Estimation
- Image Synthesis
- Object Tracking
- Image Captioning
- 3D Computer Vision
- Siamese Networks
Projects
Get complete in hand experience with industry demand projects.
Who Can Apply for This Course?
WHO CAN APPLY FOR THE COURSE?
Education should not be limited to any specific person. So we offer that courses which is designed for different people .
- Anyone with a bachelor’s degree and passion for Data Science
- Professionals looking to grow their career as a Data Science expert
- Professionals who want to transition into Data scientist
- Any IT professional with a bachelor’s degree who want to transition into Data science
- Freshers and Professionals with Non programming
Job Roles in Data Science
There are various job roles that are in high demand which you can go for .
Senior Data Scientist
Manages team and work on complete handling and designing of models.
AI Expert
Works on AI models and new products of AI for company growth.
Machine Learning Expert
Need to work on large number of data to create chunks and use latest tools to update the models.
Applied Scientist
Its compete implementation part as need to work on experiments to develop intelligence.
Big Data Specialist
Need to work on huge data with proper frameworks to filter and validate the data.
Senior Business Analyst
Get data from different media to work on business analysis and make improvements for business growth.
Why Choose Us?
Learning lab is started with a vision to provide world class curriculum to each student who want to grow career in data science.
Our Students Works At
We Offer What Industry Demands
100% Job Placement Support
Latest & Updated Syllabus
Complete Practical Based Learning
Key Insights
Excellence: A commitment to providing high quality education and training in data science through rigorous coursework, practical projects, and experienced faculty.
Innovation: An emphasis on creativity and cutting-edge research in data science, encouraging students to think critically, experiment, and explore new ideas.
Collaboration: A focus on teamwork and collaboration, recognizing the importance of working with others to solve complex problems and achieve common goals.
Diversity and inclusivity: A commitment to creating a welcoming and inclusive learning environment that values diversity and promotes equity, recognizing the importance of multiple perspectives and experiences in data science.
SOFT SKILL TRAINING FOR ALL PROGRAMS
- Verbal Communication
- Non-Verbal Communication
- Listening Skills
- Email Etiquette
- Decision-Making
- Problem-Solving
- Goal Setting
- Delegation
- Conflict Resolution
- Effective Feedback
- Goal Setting
- Task Prioritization
- Scheduling
- Procrastination Management
- Self-Awareness
- Self-Regulation
- Empathy
- Social Skills
- Stress Management
- Active Listening
- Problem-Solving
- Effective Communication
- Empathy
- Diversity and Inclusion
- Cultural Awareness
- Inclusion
- Sensitivity to Different Perspectives
- Addressing Bias
- Brainstorming Techniques
- Problem-Solving
- Critical Thinking
- Risk-Taking
- Out-of-the-Box Thinking
- Communication
- Collaboration
- Conflict Resolution
- Goal Setting
- Trust Building
- Flexibility
- Resilience
- Agility
- Change Management
- Building Relationships
- Communication
- Personal Branding
- Follow-Up Strategies
Career Services By Learning Lab
We are into creating more skilled people for high paying jobs. We network with brands to give you opportunity to reach to your dream job. There js confusion about how to reach step by step so we solve these problem by providing complete job support.
Interview preparation not only comes with tech skills it also need soft skill to crack interview in one go. We bring complete modules for soft skill preparation and give you hand hold support for personal growth.
Free Laptop: Sounds interesting! We believe in complete practical based learning so you need to have to have gadgets to practice what you learn. So we provide laptop too to practice and explore day by day.
APPLICATION PROCESS FOR ALL PROGRAMS
Get Complete
Course Details
Our platform provides a diverse range of educational resources and tools, including online courses, interactive tutorials, personalized learning paths, and career services. Our courses are designed and delivered by experts in their respective fields, covering subjects ranging from digital marketing to cyber security.
Courses
- Data Science
- Digital Marketing
- Data Analytics
- Cloud Computing
- Cyber Security
Step By Step Process - How We Help You To Prepare for Jobs
FAQ
Most frequent questions and answers
Data science is an interdisciplinary field that involves extracting insights and knowledge from structured and unstructured data usingtechniques from statistics, computer science, and machine learning.
Some of the key skills needed for a career in data science include statistical analysis, programming skills, data visualization, machine learning, and communication skills.
Python and R are the most commonly used programming languages in data science. Other programming languages such as SQL, Java, and Scala are also used.
Some of the common techniques used in data science include regression analysis, clustering, classification, and natural language processing.
Supervised learning is a machine learning technique that involves training a model on labeled data to make predictions on new data. Unsupervised learning involves finding patterns in unlabeled data.
A data pipeline is a series of steps involved in collecting, processing, and analyzing data. This typically involves data extraction, data cleaning, data transformation, and data visualization.
Data visualization involves presenting data in a graphical format to facilitate understanding and communication. Common types of data visualization include charts, graphs, and maps.
Big Data refers to large, complex datasets that are difficult to process using traditional data processing methods. Big Data is often characterized by the 3Vs: volume, velocity, and variety.
Machine learning is a subset of artificial intelligence that involves training algorithms to make predictions or decisions based on data. Machine learning algorithms can be supervised, unsupervised, or semisupervised
Data science is used in a wide range of applications, including business analytics, fraud detection, recommendation systems, medical diagnosis, and predictive maintenance.