Data Science Course in Chennai

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Data Science Course in Chennai

Data Science Course = Top career choice


Data science is an interdisciplinary field that combines programming, statistics, and business intelligence with fields like machine learning, artificial intelligence, and business analytics to get valuable information from large amounts of data.

Data science is a new and popular field with a lot of opportunities.

Data scientists are in high demand because their skills can be used in many different fields, such as Healthcare, Finance, Retail, Education, and many more. Since 2012, the demand for data scientists has grown by 31% every year. Their average salary ranges from 6 to 10 lacs per year in India, depending on the location and size of the company.

If you have good skills in Data Science, you can get jobs like Data Analyst, Business Intelligence Analyst, Data Visualizer, etc., to start with.

Data science is one of the top five careers that young people worldwide want to go into, and it's only going to get stronger in the years to come.


Why is Web D School the best training institute to learn Data Science Course in Chennai?

1. Trainers from Industry

All our trainers have gained real time experience working in reputed companies & have immense knowledge in the Data Science field.

2. Small batch size

We take only 6 students per batch so that we can pay more attention to each one.

3. Frills-free syllabus

We only teach what a student needs to know to enter the Data Science field, which is different from most institutes that try to attract students with fancy terminologies and needless topics.

4. Projects based training (SOAP)

We give our students a lot of tasks and assignments through a system we call SOAP (Student Output Assessment Plan), and we also give them helpful feedback.

5. Live Interactive sessions

Since our batch sizes are small, it would truly be an interactive session where we encourage our students to ask any number of doubts during the class.

6. Recorded sessions

All sessions would be recorded on video and given to the students so they could watch and learn from them later.

7. Placement support

We have a dedicated placement team that supports all our students in their placement journey, starting with Resume building until securing a good job.

Our Data Science course coverage





Syllabus - Data Science Course in Chennai

Data Science Courses Syllabusaa

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Module 1 : Introduction to Data Science

  • What is Data Science
  • What is Machine Learning
  • What is Deep Learning
  • What is AI?
  • Data Analytics and its types
  • Why python?
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Module 2 : Python (Basics to advanced)

  • Why python?
  • Installation and google colab setup
  • Understanding various python notebooks like jupyter,spider. spider.
  • Variables and data types: numbers, Boolean and strings
  • Operators
  • Conditional statements
  • Functions
  • Sequences
  • Files and Classes
  • Object oriented programming
  • Inheritance
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Module 3 : Python Packages

  • Numpy
  • Pandas
  • Matplotlib
  • Seaborn
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Module 4 : Statistics

  • Types of statistics
  • Descriptive statistics
  • Types of data
  • Population and sample
  • Level of measurement
  • Mean, median, mode
  • Regression
  • Variability
  • R-squared
  • Inferential statistics
  • Correlation
  • Covariance
  • Distribution
  • Normal distribution
  • Standard normal distribution
  • Central limit theorem
  • Standard error
  • Estimators and estimates
  • Confidence intervals
  • Z-score
  • Margin of errors
  • Distance Metrics
  • Hypothesis Testing
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Module 5 : Algebra

  • Algebraic equations
  • Exponents and logs
  • Polynomial equations
  • Factoring
  • Functions
  • Quadratic equations
  • Calculus foundation
  • Differentiation and derivatives
  • Vectors
  • Calculus
  • Matrix
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Module 6 : Probability

  • Basic probability
  • Computing expected values
  • Frequency
  • Events
  • Combinatorics
  • Factorials
  • Symmetry of combinations
  • Bayesian inference
  • Sets and Events
  • Probability distributions
  • Discrete distributions
  • Applications of probability in statistics
  • Applications of probability in finance
  • Applications of probability in Data Science
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Module 7 : Data Preprocessing

  • Handling missing values
  • Encoding categorical data
  • Split the dataset
  • Feature scaling
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Module 8 : Exploratory Data Analysis

  • Feature Engineering
  • Data Visualization - Tableau
  • Different chart types
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Module 9 : Machine Learning

  • Introduction to machine leaning
  • Types of AI
  • Stages of Ml projects
  • Types of Ml algorithms
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Module 10 : Regression

  • Simple linear regression
  • Multi linear regression
  • Model Evaluation
  • Project : Kaggle bike demand prediction
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Module 11 : Classification

  • Logistics regression
  • SVM
  • KNN
  • DECISION TREES
  • RANDOM FOREST
  • XG BOOST CLASSIFIER
  • NAÏVE BAYES
  • Model Evaluation
  • Project : open Kaggle competition project
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Module 12 : Clustering

  • K means cluster
  • Hierarchical clustering
  • model evaluation
  • parameter tunning
  • model visualization
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Module 13 : Model Tuning

  • Hyperparameter Optimization
  • Grid Search
  • Random Grid Search
  • Bayesian Optimization
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Module 14 : Recommendation System

  • Content-based filtering
  • Collaborative based filtering
  • Market basket Analysis
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Module 15 : Databases

  • SQL
  • Mongodb
  • Introduction to Cloud
  • Cloud storage
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Module 16 : Deep Learning

  • Tensor flow and Keras
  • Deep learning frame work
  • Artificial neural network
  • Natural language processing
  • Conventional neural network
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Module 17 : Flask

  • Creating RestFul API with Flask
  • Postman / ARC Chrome
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I genuinely loved the data science course offered here. The course was very helpful for someone like myself who wanted to transition to data science from a non-IT domain. The syllabus was well-tailored and covered everything from basic all the way till advanced topics. The instructors were very knowledgeable and made the classes more engaging.

-Kaushik N