Software Training Institute in Chennai with 100% Placements – SLA Institute

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Data Science Full Stack Course in OMR

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Live Online & Classroom Training
EMI
0% Interest

Explore SLA Institute’s dynamic Data Science Full Stack Training in OMR, where you’ll master front-end and back-end data processing. Dive into Python, R, machine learning, and cutting-edge data visualization tools like TensorFlow and pandas. With hands-on projects and personalized career support, prepare for exciting opportunities in data analysis and machine learning engineering. Our program guarantees Lifetime placement assistance, empowering you to launch a successful career in the fast-paced realm of data science. Join SLA Institute today and embark on a transformative journey towards becoming a skilled data professional with our Data Science Full Stack Course with 100% Placement Support.

At SLA Institute, we guarantee placement in a high-paying Scientist job with the support of our experienced placement officers. Our Data Science Full Stack Course Syllabus covers all essential topics, providing you with a comprehensive understanding of Data Science Full Stack development.

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Upcoming Batches

Hands On Training
3-5 Real Time Projects
60-100 Practical Assignments
3+ Assessments / Mock Interviews
September 2024
Week days
(Mon-Fri)
Online/Offline

2 Hours Real Time Interactive Technical Training 

1 Hour Aptitude 

1 Hour Communication & Soft Skills

(Suitable for Fresh Jobseekers / Non IT to IT transition)

Course Fee
September 2024
Week ends
(Sat-Sun)
Online/Offline

4 Hours Real Time Interactive Technical Training

(Suitable for working IT Professionals)

Course Fee

Save up to 20% in your Course Fee on our Job Seeker Course Series

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Quick Enquiry

Placement

100% Assistance

Learning

Job-Centered Approach

Timings

Convenient Hrs

Mode

Online & Classroom

Certification

Industry-Accredited

This Course Includes

  • FREE Demo Class
  • 0% EMI Loan Facilities
  • FREE Softskill & Placement Training
  • Tie up with more than 500+ MNCs & Medium Level Companies
  • 100% FREE Placement Assistance
  • Course Completion Certificate
  • Training with Real Time Projects
  • Industry-Based Coaching By MNC IT Professionals
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Expected Criteria for Assured Placement

The following criteria help the placement team guide the candidates to get placed immediately after the course completion through SLA Institute.

  • 80% of coursework completion helps us arrange interviews in required companies.
  • 2 or 3 projects to be done for the selected course to ace the technical round effectively.
  • Ensure attending the placement training right from the first day of the selected course.
  • Practice well with resume building, soft skill, aptitude skill, and profile strengthening.
  • Utilize the internship training program at SLA for the complete technical skills.
  • Collect the course completion certificate and update the copy to the placement team.
  • Ensure your performance indicator meets the expectation of top companies.
  • Always be ready with the updated resume that includes project details done at SLA.
  • Enjoy unlimited interview arrangements along with internal mock interviews.
Have Queries? Ask our Experts

+91 89256 88858

SLA's Distinctive Placement Approach

1

Tech Courses

2

Expert Mentors

3

Assignments & Projects

4

Grooming sessions

5

Mock Interviews

6

Placements

Objectives of Data Science Full Stack Course in OMR

The Data Science Full Stack Course at SLA Institute in OMR focuses on teaching essential skills for full-stack development using Data Science. Students will learn:

  • Learn Programming Languages: Master Python and R for data manipulation and analysis.
  • Understand Data Handling: Cover data collection, cleaning, and storage methods.
  • Explore Advanced Techniques: Study machine learning, deep learning, NLP, and image recognition.
  • Practice with Projects: Gain hands-on experience through practical projects.
  • Prepare for Careers: Receive 100% placement support for roles in data analysis and machine learning.

Future Scope of Data Science Full Stack Course in OMR

  • Expanding Career Opportunities

The Data Science Full Stack Course in OMR opens doors to many job opportunities in industries like healthcare, finance, and e-commerce. Roles such as data analyst, machine learning engineer, and business intelligence analyst are in demand and offer good career growth and pay.

  • Technological Advancements

As technology like artificial intelligence and machine learning advances, skills in data science become even more valuable. Companies use these technologies for smarter decisions and automation, so knowing data processing, predictive modeling, and data visualization is crucial.

  • Industry Demand

Businesses rely more on data for insights, so there’s a growing need for skilled data professionals. This trend fuels demand for people who can handle big data and set up effective data systems using cloud computing.

  • Continuous Learning and Adaptation

Data science is always changing, so it’s important for professionals to keep learning new tools and techniques. Graduates of the Data Science Full Stack Course in OMR learn not just basic skills but also how to stay updated and adapt to new technology trends.

  • Global Opportunities

Data science skills are useful worldwide, allowing professionals to work internationally or remotely. Those trained at SLA Institute in OMR can explore job markets globally and contribute to projects across different countries, using their expertise in data analysis and machine learning to drive innovation everywhere.

Achieve Your Goals With SLA

SLA builds your future with comprehensive coursework and unparalleled placement support.
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Data Science Full Stack Course Syllabus

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Enroll in our Data Science Full Stack Training at SLA Institute in OMR to acquire essential skills for developing dynamic applications using Data Science. From mastering programming fundamentals to exploring frameworks like Spring and Hibernate, and learning about databases and deployment strategies, you’ll gain valuable expertise in demand by employers. With practical projects and SLA Institute’s dedicated placement support, you’ll feel confident to start a rewarding career in Data Science and web development.

CORE PYTHON
  • Python Introduction & history
  • Color coding schemes
  • Salient features & flavors
  • Application types
  • Language components (variables, literals, operators, keywords…)
  • String handling management
    1. String operations – indexing, slicing, ranging
    2. String methods – concatenation, repetition, formatting
    3. Supporting functions
  • Native data types
    1. List
    2. Tuple
    3. Set
    4. Dictionary
  • Decision making statements
    1. If
    2. If…else
    3. If…elif…else
  • Looping statements
    1. For loop
    2. While loop
  • Function types
    1. Built-in functions
    2. Math functions
    3. User defined functions
    4. Recursive functions
    5. Lambda functions
  • OOPs
    1. Classes and objects
    2. __init__ constructor
    3. Self-keyword
    4. Data abstraction
    5. Data encapsulation
    6. Polymorphism
    7. Inheritance
  • Exception handling
    1. Error vs exception
    2. Types of error
    3. User defined exception handling
    4. Exception handler components
    5. Try block, except block, finally block
  • File handling
    1. How to create a txt file using python
    2. File access modes
    3. Reading and writing data to a txt file
    4. Data operations
DATA SCIENCE PHASE 1
  • Working with PANDAS & NUMPY
    1. PANDAS – data analysis intro
    2. PANDAS – data structures
    3. Series creation types
    4. Data Frame creation types
    5. Accessing data from Series and DataFrame
    6. Data merging
  • Working with PANDAS & NUMPY
    1. Data mapping
    2. Finding duplicates
    3. Removing duplicates
    4. Describing data
    5. Finding null values
    6. Group by function
    7. Sort values
    8. Statistical functions
    9. Reading and writing data from CSV
    10. Data operations on CSV file
    11. Basic visualizations
    12. NUMPY array processing intro
    13. Types of ndarray
  • Numpy attributes
    1. ndim
    2. shape
    3. size
    4. type
  • Shape manipulations
    1. Ravel
    2. Reshape
    3. Resize
    4. Hsplit
    5. Vstack
  • Numpy additional functions
    1. Tile
    2. Eye
    3. Zeros
    4. Ones
    5. Diag
    6. arange
    7. New axis addition
    8. Random number generation
DATA SCIENCE PHASE 2
  • Data science terminologies
  • Exploratory data analysis intro
  • Types of machine learning algorithms
  • Classification and regression intro
  • Prediction and analysis techniques to be used in ML
  • MATPLOTLIB – data visualization
    1. Histogram
    2. Pdf
    3. Adding axes
    4. Adding grid
    5. Adding label
    6. Adding ticks
    7. Setting limits
    8. Adding legend
  • MATPLOTLIB plotting
    1. Bar chart
    2. Pie chart
    3. Heat map
    4. Box plot
    5. Scatter plot
    6. 3d plot
  • SEABORN – advanced color palette visualization
    1. Bar chart
    2. Pie chart
    3. Dist plot
    4. Pair plot
    5. Reg plot
    6. Count plot
    7. Swarmplot
    8. Heat map
    9. Scatter plot
    10. Lm plot
EDA – MACHINE LEARNING –WORKING WITH SCIKIT-LEARN
  • Machine learning algorithm types
    1. Supervised learning
    2. Unsupervised learning
    3. Ensemble learning technique
  • Working flow of dataset
    1. Loading necessary modules
    2. Loading dataset
    3. Feature scaling
    4. Feature extraction
    5. Data standardization
    6. Data normalization
    7. Data manifesting
    8. Model creation
    9. Fitting data models
    10. Model prediction
  • ML algorithms with live demo and mathematical intuition
    1. Linear regression
    2. Logistic regression
    3. Naïve bayes classifier
    4. KNN (K nearest neighbor)
    5. KMC (K means clustering)
    6. Support vector machines
    7. Principal component analysis
    8. Decision tree
    9. Random forest
    10. XGBoost
DEEP LEARNING & AI
  • Neural networks introduction
  • Brain activation functions and layer components
  • Neural network terminologies of ANN, CNN, RNN
    1. Models
    2. Initializers
    3. Optimizers
    4. Layers
    5. Activation functions
    6. Loss functions
    7. Metrics
    8. Model compilations
    9. Model evaluation
    10. Max pooling layers
    11. Edge filters
    12. Back propagations
    13. Early stopping
    14. Epoch
  • Datasets to be used for MLP,ANN, CNN,RNN
    1. Boston house prediction
    2. CIFAR10
    3. CIFAR100
    4. MNIST
    5. FASHION MNIST
    6. IMDB Movie review analysis
  • NLP (Natural Language Processing)
    1. NLTK
    2. NLTK
    3. SPACY
  • COMPUTER VISION
    1. Digital Image Processing using CV2 library
    2. LIVE PROJECTS

Project Practices on Data Science Full Stack Training

Project 1Exploratory Data Analysis (EDA)

Students explore datasets using graphs and statistics to find patterns and insights. They learn to use tools like matplotlib and seaborn for visualizations, helping them understand data better.

Project 2Predictive Modeling

Students build models to predict outcomes from data using algorithms like regression and decision trees. This helps them learn how to make predictions based on historical data.

Project 3Natural Language Processing (NLP) Application

Students create programs that analyze and understand text data. They learn techniques like figuring out feelings in text (sentiment analysis) or sorting text into categories (text classification).

Project 4Big Data Analysis

Students work with large datasets using tools like Apache Spark. They learn to clean data, create useful features, and train models. This helps them handle big amounts of data effectively for analysis and decision-making.

Prerequisites for learning Data Science Full Stack Course in OMR

To join our Data Science Full Stack Training in OMR at SLA Institute, no specific prior knowledge is required. Whether you’re new to programming or have some experience, everyone is welcome. However, having a basic understanding of the following can be beneficial:

  • Basic Programming: Knowing Python or R is useful for data manipulation.
  • Math and Statistics: Understanding concepts like algebra and statistics aids in learning machine learning techniques.
  • Data Analysis: Familiarity with data cleaning, transformation, and visualization basics supports understanding advanced data science methods.

These concepts can enhance your learning experience but are not required to enroll or succeed in our Data Science Full Stack Course at SLA Institute in OMR.

Our Data Science Full Stack Course in OMR is ideal to:

  • Students eager to excel in Data Science Full Stack
  • Professionals considering transitioning to Data Science Full Stack careers
  • IT professionals aspiring to enhance their Data Science Full Stack skills
  • Data Analysts enthusiastic about expanding their expertise
  • Individuals seeking opportunities in Data Science Full Stack

Job Profile in Data Science Full Stack Course in OMR

In the Data Science Full Stack Course at SLA Institute in OMR, participants are prepared for various job profiles that require expertise in both front-end and back-end data handling:

  • Data Analyst: Responsible for analyzing data to uncover patterns and trends, creating reports to support decision-making. Average salary ranges from ₹3.5-5.5 lakhs per annum.
  • Machine Learning Engineer: Designs and deploys machine learning models to automate predictive analytics tasks. Can earn between ₹6-10 lakhs annually.
  • Data Scientist: Utilizes statistical analysis and machine learning techniques to derive insights and solve complex business problems. Average salaries range from ₹7-12 lakhs per year.
  • Business Intelligence Analyst: Transforms data into actionable intelligence for strategic planning and operational improvements. Salaries typically range from ₹4-7 lakhs annually.
  • Big Data Engineer: Designs and maintains large-scale data processing systems for efficient handling and analysis of big data. Can earn between ₹8-15 lakhs per annum.

These roles require proficiency in programming languages like Python and R, data visualization tools, and machine learning algorithms taught in the course. Graduates are equipped for rewarding careers in the data-driven industry with competitive salary prospects.

Want to learn with a personalized course curriculum?

The Placement Process at SLA Institute

  • To Foster the employability skills among the students
  • Making the students future-ready
  • Career counseling as and when needed
  • Provide equal chances to all students
  • Providing placement help even after completing the course

Data Science Full Stack Course FAQ

What is the Data Science full-stack?

The Data Science full-stack involves learning all aspects of data science, from analyzing data and using programming languages like Python and R, to understanding statistics, machine learning, data visualization, and managing large amounts of data for solving complex problems.

Is Data Science full stack easy or hard?

Learning Data Science full stack can be tough because it covers many areas like programming, statistics, and machine learning. But with effort and focused learning, it can be learned well, leading to promising opportunities in data-related careers.

What is Data Science used for?

Data Science is used to analyze and extract insights from large sets of data. It helps businesses make informed decisions, predict trends, optimize processes, and develop new products or services based on data-driven insights.

Is Data Science enough to get a job?

Having skills in Data Science can help you find a job, especially in areas like data analysis, machine learning, and artificial intelligence. However, some jobs might need you to know other specific tools or programming languages too, depending on what the employer wants.

Does SLA Institute have HR personnel?

Yes, SLA Institute has an HR personnel who will look into students issues and grievances.

Does SLA Institute support EMI options?

Yes, SLA Institute supports EMI options with 0% interest.’

Is Data Science Full Stack a good career?

Data Science Full Stack can lead to a rewarding career because it’s in demand across industries like technology, finance, and healthcare. Learning both front-end and back-end skills prepares you to solve complex data problems and create innovative solutions.

Does SLA Institute provide Lifetime Placement Support?

Yes, SLA Institute provides Lifetime Placement Support to assist students in securing job placements throughout their careers.

On Average Students Rated The Data Science Full Stack Course 4.80/5.0
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