At Eddoc Technology, we offer world-class Data Science Training Programs designed to help you master the art of data analysis, machine learning, and artificial intelligence. Whether you are a fresher, working professional, or an entrepreneur, our hands-on training approach ensures you gain the expertise needed to excel in today's data-driven world.

Data Science Training Course

Key Features of DATA SCIENCE

50+ live sessions spread around seven months

Hands-On Projects with Real-World Datasets

Expert Instructors with Industry Experience

Practical Experience with Popular ML Tools and Frameworks

Resume Preparation and LinkedIn Profile Review

Career Guidance and Placement Assistance

COURSE CURRICULUM

Module 1: Introduction to Data Science

➤ What is Data Science?
➤ The Data Science Lifecycle
➤ Applications and Trends in Data Science
➤ Skills and Tools for Data Science

Module 2: Programming for Data Science

Python/R Programming:

➤ Basics of Python/R: Data Types, Variables, and Operations
➤ Control Structures: Loops and Conditionals
➤ Functions and Modules
➤ Working with Libraries (NumPy, Pandas, dplyr, etc.)
➤ Data Input and Output

Module 3: Statistics and Probability

➤ Descriptive Statistics: Mean, Median, Mode, Variance
➤ Inferential Statistics: Hypothesis Testing, Confidence Intervals
➤ Probability Distributions: Normal, Binomial, Poisson
➤ Correlation and Regression Analysis

Module 4: Data Wrangling and Preparation

➤ Data Cleaning Techniques
➤ Handling Missing Data
➤ Data Transformation and Normalization
➤ Feature Engineering
➤ Outlier Detection and Treatment

Module 5: Data Visualization

➤ Introduction to Data Visualization
➤ Creating Charts and Graphs with Matplotlib, Seaborn, and ggplot2
➤ Interactive Dashboards with Tableau or Power BI
➤ Storytelling with Data

Module 6: Machine Learning

Supervised Learning:

➤ Linear and Logistic Regression
➤ Decision Trees and Random Forests
➤ Support Vector Machines (SVM)
➤ k-Nearest Neighbors (kNN)
➤ Gradient Boosting (XGBoost, LightGBM)

Unsupervised Learning:

➤ Clustering (K-Means, Hierarchical Clustering)
➤ Dimensionality Reduction (PCA, t-SNE)

Model Evaluation and Tuning:

➤ Train/Test Split
➤ Cross-Validation
➤ Hyperparameter Tuning

Module 7: Advanced Topics in Machine Learning

➤ Ensemble Methods
➤ Time Series Analysis
➤ Recommendation Systems
➤ Model Deployment with Flask or Streamlit

Module 8: Big Data and Cloud Computing

➤ Introduction to Big Data and Hadoop
➤ Working with Spark for Large-Scale Data Processing
➤ Data Science on Cloud Platforms (AWS, GCP, Azure)

Module 9: Deep Learning

➤ Introduction to Neural Networks
➤ Convolutional Neural Networks (CNNs) for Image Processing
➤ Recurrent Neural Networks (RNNs) for Sequential Data
➤ Natural Language Processing (NLP) Basics

Module 10: Tools and Technologies

➤ Git and Version Control
➤ Jupyter Notebooks for Data Science
➤ SQL for Data Extraction and Manipulation
➤ APIs for Data Retrieval

Module 11: Real-World Projects and Capstone

➤ End-to-End Data Science Project Lifecycle
➤ Industry-Specific Use Cases (e.g., E-commerce, Healthcare, Finance)
➤ Model Deployment and Monitoring

📞FOR ENQUIRY

Become a Data Science Professional in Just 4 Month

FAQ: Data Science at Eddoc Technology

1. What is Data Science, and why should I learn it?

Data Science is the field of extracting insights and knowledge from structured and unstructured data using scientific methods, algorithms, and tools. Learning Data Science equips you with skills to analyze data, solve real-world problems, and make data-driven decisions, making it a highly in-demand career choice.

2. Who can enroll in the Data Science course at Eddoc Technology?

Our Data Science course is designed for:
➤ Fresh graduates seeking a career in data-driven roles.
➤ IT professionals looking to upskill or transition into Data Science.
➤ Business professionals aiming to enhance their decision-making skills.
➤ Entrepreneurs who want to leverage data for business growth.

No prior coding or technical background is required as we start from the basics.

3. How is the training conducted?

We offer flexible learning modes to suit your convenience:.
➤ Online Training: Live instructor-led classes from the comfort of your home.

4. Are there any prerequisites for this course?

No specific prerequisites are required. However, having basic knowledge of mathematics, statistics, or programming is helpful.

5. What kind of projects will I work on?

You will work on hands-on projects in domains such as:
➤ Predictive analytics for e-commerce.
➤ Fraud detection in banking.
➤ Healthcare data analysis for patient insights.
➤ Building recommendation systems.

These projects help you build a portfolio showcasing your expertise.

6. Will I get a certificate upon completing the course?

Yes! Upon successfully completing the course, you will receive a Data Science Certification from Eddoc Technology, recognized by industry leaders.

7. Do you offer placement assistance?

Absolutely! Our placement support includes:
➤ Resume-building workshops.
➤ Mock interviews and technical guidance.
➤ Job referrals through our extensive industry network.

Many of our students have successfully secured roles in leading companies.

© 2024 Eddoc Technology. All rights reserved