Edureka learning center delivers an immersive Data Science Course in Coimbatore, arming learners with state-of-the-art expertise in AI, machine learning, and big data analytics. Spearheaded by seasoned industry professionals, the curriculum seamlessly integrates theoretical principles with hands-on applications, fostering a profound grasp of industry-relevant solutions.

Data Science Courses in EDUREKA

Data Science Course In Coimbatore – Why Edureka?

Seeking to excel in Data Science in Coimbatore? Edureka learning center stands as the premier hub for ambitious professionals. With a meticulously structured curriculum, expert-guided instruction, and immersive project-based learning, it equips students with industry-relevant expertise. Under the mentorship of seasoned specialists, learners delve into Python, Machine Learning, and AI, mastering the tools that drive innovation. The academy extends comprehensive career assistance, bridging the gap between talent and top-tier employers. Whether you prefer a virtual or in-person learning environment, flexible options cater to diverse needs. Step into the dynamic realm of data science—enroll now and forge a future brimming with opportunity!

Data Science Overview

Data Science is an interdisciplinary domain that fuses statistical analysis, machine learning, programming, and industry acumen to derive actionable intelligence from both structured and unstructured data. It serves as a cornerstone for strategic decision-making, process automation, and predictive analytics across sectors such as healthcare, finance, and e-commerce At its foundation, Data Science Overview encompasses data acquisition, preprocessing, exploratory analysis, and visualization, culminating in the development of predictive models through sophisticated algorithms. Cutting-edge technologies like Python, R, SQL, TensorFlow, and cloud computing empower modern enterprises to harness the full potential of data. These insights drive customer behavior predictions, fraud mitigation, personalized recommendations, and operational enhancements. As organizations deepen their reliance on big data, VNET recognizes how Data Science continues to evolve, integrating artificial intelligence, deep learning, and real-time analytics. The demand for skilled professionals—Data Analysts, Machine Learning Engineers, and Data Scientists—has surged globally. With businesses adopting data-centric strategies, expertise in Data Science unlocks a wealth of high-impact career opportunities.

We collaborate with 200+ leading IT companies of all cities in India

Inexperienced Fresher Becomes an Data Science Professionals

Stepping into the realm of data science can feel overwhelming, but the right guidance turns beginners into industry-ready professionals. Edureka learning center empowers freshers with the expertise needed to seamlessly transition into this dynamic field. Through immersive projects, mentorship from seasoned experts, and real-world case studies, learners gain hands-on experience in machine learning, artificial intelligence, big data analytics, and programming. The meticulously designed curriculum unravels the intricacies of data collection, preprocessing, modeling, and visualization, making even complex concepts approachable. Personalized mentorship accelerates learning, ensuring freshers build confidence and competence. With dedicated career support and job placement assistance, aspiring professionals secure opportunities in leading organizations.

Our Training Methology

Methology 1

Industry-Expert Instruction – Learn from seasoned professionals with hands-on experience in data science training in Coimbatore.

Methology 2

Immersive Practical Projects – Engage in real-world applications to build expertise.

Methology 3

Tailored Mentorship – Receive individualized guidance to accelerate growth.

Methology 4

State-of-the-Art Technologies – Master the latest tools shaping the industry.

Methology 5

Adaptive Learning Modes – Choose between online and in-person training with VNET.

Methology 6

Live Industry Case Studies – Solve complex, real-time business challenges.

Methology 7

Comprehensive Career Support – Gain assistance in securing top job opportunities.

What are the Career Benefits of Learning Data Science Certification Course at Edureka

Benefit 1

Elite Training – Gain knowledge from industry veterans with extensive expertise in data science training in Coimbatore.

Benefit 2

Practical Immersion – Work on hands-on projects that mirror real-world applications.

Benefit 3

Adaptive Learning – Choose between online and offline modes for seamless education at VNET.

Benefit 4

Advanced Technologies – Master cutting-edge tools driving modern innovations.

Benefit 5

Customized Mentorship – Receive tailored guidance to accelerate your growth.

Benefit 6

Real-World Case Studies – Analyze industry-specific challenges and develop strategic solutions.

Benefit

Career Advancement – Access job placement assistance to secure top opportunities.

Aspiring to master data science training in Coimbatore? Edureka learning center welcomes you. Whether you’re a recent graduate eager to step into the tech world, a professional looking for a career transformation, or an entrepreneur striving to leverage data-driven strategies, this program is designed for you. IT specialists, analysts, engineers, and business leaders can acquire cutting-edge skills in machine learning, AI, and big data analytics. With a meticulously crafted curriculum, hands-on projects, and expert guidance, learners cultivate real-world problem-solving expertise. Dive into premier learning at Edureka learning center and unlock endless possibilities in the dynamic realm of data science.

Who can join this course? Immerse Yourself in World-Class Learning at Vnet Academy - Edureka Learning Center

About Classroom Training

Step into an engaging, high-impact learning environment at Edureka learning center, where classroom training bridges the gap between theory and hands-on application. Led by seasoned industry professionals, each session delves deep into data science, AI, machine learning, and big data analytics, equipping learners with practical, job-ready skills. Housed within a cutting-edge learning facility, students participate in dynamic discussions, real-world projects, and collaborative problem-solving that reinforce core concepts. Personalized mentorship ensures seamless comprehension of intricate topics, fostering confidence and expertise. For those who thrive on face-to-face interaction, this structured training approach promotes engagement, professional networking, and instant feedback. Explore data science course fees in Coimbatore and unlock opportunities for a successful career in the evolving data science landscape.

FAQ

Who is eligible to join the data science training at Edureka learning center?

Aspiring data professionals, including students, IT experts, career changers, and entrepreneurs, are welcome to enroll.

What learning formats are offered?

We provide both in-person classroom training and flexible online sessions, catering to different learning preferences.

Is prior coding knowledge required?

Not at all. Our curriculum is structured to support both beginners and professionals seeking to enhance their expertise.

Will I receive a certification after completing the course?

Yes, participants receive an industry-recognized certification, validating their skills and expertise.

Does Edureka learning center offer job placement support?

Absolutely. We provide career guidance, resume refinement, and interview preparation to help secure top industry positions.

What Will You Learn

Core Principles of Data Science – Grasp essential theories, analytical frameworks, and real-world applications.
AI & Machine Learning Mastery – Develop intelligent models and harness the power of artificial intelligence.
Big Data Processing – Efficiently handle, analyze, and derive insights from vast datasets.
Advanced Data Visualization – Convert complex data into clear, actionable visual narratives.
Coding for Data Science – Strengthen your expertise in Python, R, and SQL for seamless data manipulation.
Industry-Specific Case Studies – Tackle real-world challenges and craft data-driven solutions.

Data Science Syllabus

Module 1

Learning Units:

• Day 1

Lu1 – Applications Of Data Science
Lu2 – Introduction To Python

• Day 2

Lu1 – Operators And Variables In Python
Lu2 – Data Types In Python

• Day 3

Lu1 – Control Flow In Python
Lu2 – Control Flow In Python

• Day 4

Lu1 – Functions In Python
Lu2 – Functions In Python

• Day 5

Lu1 – Packages And Modules In Python
Lu2 – File Handling In Python

Day 6

Lu1 – Introduction To Numpy Arrays
Lu2 – Basic Numpy Operations

• Day 7

Lu1 – Numpy Functions
Lu2 – Indexing And Slicing Of Numpy Arrays

• Day 8

Lu1 – Array Manipulation In Python
Lu2 – Array Manipulation In Python

• Day 9

Lu1 – File Handling Using Numpy
Lu2 – Numpy Case Study

• Day 10

Lu1 – Introduction To Pandas Library In Python
Lu2 – Pandas Data Structures

• Day 11

Lu1 – Importing And Exporting Data Using Pandas
Lu2 – Functionality Of Pandas Series

• Day 12

Lu1 – Functionality Of Pandas Dataframes
Lu2 – Functionality Of Pandas Dataframes

• Day 13

Lu1 – Combining Data Using Pandas
Lu2 – Combining Data Using Pandas

• Day 14

Lu1 – Data Cleaning Using Pandas
Lu2 – Data Cleaning Using Pandas

• Day 15

Lu1 – Grouping Data Using Pandas
Lu2 – Grouping Data Using Pandas

• Day 16

Lu1 – Data Visualization Library – Matplotlib
Lu2 – Data Visualization Library – Seaborn

• Day 17

Lu1 – Visualizing Matplotlib Plots And Charts
Lu2 – Customizing Visualizations And Saving Plots

• Day 18

Lu1 – Introduction To Web Scraping
Lu2 – Web Scraping Using Beautiful Soup

Module 2

Learning Units:

• Day 19

Lu1 – Statistical Analysis In Data Science
Lu2 – Measures Of Central Tendency

• Day 20

Lu1 – Measures Of Dispersion
Lu2 – Measures Of Position

• Day 21

Lu1 – Univariate Non-graphical Eda
Lu2 – Univariate Graphical Eda

• Day 22

Lu1 – Multivariate Non-graphical Eda
Lu2 – Multivariate Graphical Eda

• Day 23

Lu1 – Introduction To Probability Theory
Lu2 – Probability Events

• Day 24

Lu1 – Types Of Probabilities
Lu2 – Bayes’ Theorem

• Day 25

Lu1 – Probability Distributions
Lu2 – Skewness And Kurtosis

• Day 26

Lu1 – Types Of Probability Distributions
Lu2 – Sampling Distributions

• Day 27

Lu1 – Inferential Statistics
Lu2 – Confidence Interval

• Day 28
Lu1 – Statistical Hypothesis Testing
Lu2 – P-value And Critical Value

• Day 29

Lu1 – Hypothesis Tests
Lu2 – T–tests

• Day 30

Lu1 – Chi–squared Tests
Lu2 – Probability And Statistics Case Study

Module 3

Learning Units:

• Day 31

Lu1 – Introduction To Machine Learning
Lu2 – Types Of Machine Learning

• Day 32

Lu1 – Data Pre-processing Techniques
Lu2 – Data Pre-processing Techniques

• Day 33

Lu1 – Testing And Training Data
Lu2 – Supervised Learning: Regression

• Day 34

Lu1 – Linear Regression
Lu2 – Calculation Of R Square

• Day 35

Lu1 – Gradient Descent
Lu2 – Regularization Techniques

Day 36

Lu1 – Regression Case Study
Lu2 – Classification Algorithms

• Day 37

Lu1 – Logistic Regression
Lu2 – Decision Tree

• Day 38

Lu1 – Decision Trees With Cart Algorithm
Lu2 – Decision Trees With Cart Algorithm

• Day 39

Lu1 – Random Forest
Lu2 – Performance Measurements

• Day 40

Lu1 – Naïve Bayes Classification
Lu2 – How Naïve Bayes Works?

• Day 41

Lu1 – K Nearest Neighbor
Lu2 – K In Knn Algorithm

• Day 42

Lu1 – Support Vector Machine
Lu2 – Non-linear Svms

Module 4

Learning Units:

• Day 43

Lu1 – Introduction To Natural Language Processing (Nlp)
Lu2 – Natural Language Tool-kit (Nltk)

• Day 44

Lu1 – Text Pre-processing
Lu2 – Text Pre-processing

• Day 45

Lu1 – Text Pre-processing
Lu2 – Text Pre-processing

• Day 46

Lu1 – Feature Extraction
Lu2 – Feature Extraction

• Day 47

Lu1 – Sentiment Analysis
Lu2 – Case Study – Sentiment Analysis

Module 5

Learning Units:

• Day 48

Lu1 – Dimensionality Reduction
Lu2 – Principal Component Analysis (Pca)

• Day 49

Lu1 – Linear Discriminant Analysis (Lda)
Lu2 – Other Techniques Of Dimensionality Reduction

• Day 50

Lu1 – Unsupervised Learning Using Clustering
Lu2 – Hierarchical Clustering

• Day 51

Lu1 – K Means Clustering
Lu2 – K Means Clustering

• Day 52

Lu1 – Fuzzy C Means Clustering
Lu2 – Dbscan Clustering

Day 53

Lu1 – Association Rule Mining
Lu2 – Generating Association Rules

• Day 54

Lu1 – Apriori Algorithm
Lu2 – Market Basket Analysis

• Day 55

Lu1 – Recommendation Engine
Lu2 – Types Of Recommender System

• Day 56

Lu1 – Recommending Similar Movie To The User
Lu2 – Introduction To Time Series

• Day 57

Lu1 – Types Of Data
Lu2 – Checks For Stationarity Of Data

• Day 58

Lu1 – Convert Non-stationary Data To Stationary Data
Lu2 – Time Series Models

• Day 59

Lu1 – Time Series Models Using Python
Lu2 – Case Study – Association Rule Mining And Time Series

Module 6

Learning Units:

• Day 60

Lu1 – Model Selection
Lu2 – K-fold Cross Validation

• Day 61

Lu1 – Model Evaluation
Lu2 – Model Evaluation Metrics For Regression

• Day 62

Lu1 – Model Evaluation Metrics For Classification
Lu2 – Calculating A Confusion Matrix

• Day 63

Lu1 – Roc And Auc
Lu2 – Precision, Recall And F1 Score

• Day 64

Lu1 – Hyperparameter Tuning
Lu2 – Hyperparameter Optimization

• Day 65

Lu1 – Perform Grid Search
Lu2 – Ensemble Learning

• Day 66

Lu1 – Bagging
Lu2 – Boosting

• Day 67

Lu1 – Adaboost
Lu2 – Adaboost

• Day 68

Lu1 – Gradient Boosting
Lu2 – Xgboost

• Day 69

Lu1 – Model Optimization
Lu2 – Linear Programming

• Day 70

Lu1 – Formulating Optimization Problem
Lu2 – Predicting Promotion Using Boosting Techniques

Module 7

Learning Units:

• Day 71

Lu1 – Introduction To Deep Learning
Lu2 – Introduction To Neural Networks

• Day 72

Lu1 – Single Layer Perceptron
Lu2 – Multilayer Perceptron (Mlp)

• Day 73

Lu1 – How Does A Neural Network Learn?
Lu2 – Backpropagation

• Day 74

Lu1 – Introduction To Tensorflow
Lu2 – Mnist Digit Classification Using Tensorflow 2.x

• Day 75

Lu1 – Understanding Cnn
Lu2 – Image Recognition

Day 76

Lu1 – Introduction To Rnn
Lu2 – Architecture Of Rnn

• Day 77

Lu1 – Understanding Rnn
Lu2 – Drawback Of Backpropagation

• Day 78

Lu1 – Lstm – Long Short-term Memory Networks
Lu2 – Understanding Lstm Structure

• Day 79

Lu1 – Introduction To Reinforcement Learning (Rl)
Lu2 – Understanding Reinforcement Learning

• Day 80

Lu1 – Rl Agent Taxonomy
Lu2 – Openai Gym

Module 8

Learning Units:

• Day 81

Lu1 – Introduction To Tableau
Lu2 – Data Connections And Charts

• Day 82

Lu1 – Data Granularity And Sorting
Lu2 – Data Grouping And Filtering

• Day 83

Lu1 – Data Blending
Lu2 – Joins And Unions

• Day 84

Lu1 – Calculations In Tableau
Lu2 – Functions In Tableau

• Day 85

Lu1 – Table Calculations And Parameters
Lu2 – Lod Calculations

• Day 86

Lu1 – Trend Lines And Reference Lines
Lu2 – Forecasting And Clustering

• Day 87

Lu1 – Introduction To Mapping
Lu2 – Web Mapping Service (Wms)

• Day 88

Lu1 – Using Charts Effectively
Lu2 – Introduction To Dashboards In Tableau

• Day 89

Lu1 – Dashboard Layouts And Formatting
Lu2 – Interactive Dashboards

• Day 90

Lu1 – Story Points In Tableau
Lu2 – Visual Best Practices

A leading IT training Institute in Coimbatore providing high-quality IT courses

Data Science Courses in EDUREKA

Data Science Course In Coimbatore – Why Edureka?

Data Science Overview

Certification

LIVE Project

Affordable Fees

Placement Support

We collaborate with 200+ leading IT companies of all cities in India

Inexperienced Fresher Becomes an Data Science Professionals

Our Training Methology

Methology 1

Methology 2

Methology 3

Methology 4

Methology 5

Methology 6

Methology 7

What are the Career Benefits of Learning Data Science Certification Course at Edureka

Benefit 1

Benefit 2

Benefit 3

Benefit 4

Benefit 5

Benefit 6

Benefit

Who can join this course? Immerse Yourself in World-Class Learning at Vnet Academy - Edureka Learning Center

Who Wants to Become a Data Science Developer?

Students and Recent Graduates in Tech Fields

Freelancers Elevating Their Skill Set:

Tech Enthusiasts Looking to Learn Modern Data Science

About Classroom Training

FAQ

Who is eligible to join the data science training at Edureka learning center?

What learning formats are offered?

Is prior coding knowledge required?

Will I receive a certification after completing the course?

Does Edureka learning center offer job placement support?

What Will You Learn

Data Science Syllabus

Module 1

Module 2

Module 3

Module 4

Module 5

Module 6

Module 7

Module 8

VNET COURSE

COIMBATORE OFFICE

TIRUPUR OFFICE