Data Science and Machine Learning Program 

Build your career in Data Science and Machine Learning

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EMI Starting at

₹ 6,083 / month

Total Program Fee

₹ 36,500
Next Batch Starts: 24 Feb, 2022

Limited no. of seats available

Program Duration: 6 Months

At 10-15 hours/week

Learning Mode

Online

Key Highlights of the Data Science Program

Succeed as a new-age data scientists career with our comprehensive project-based learning program. This program will help you to build solid foundation of data science and machine learning and working on real project at production level,  internship-grade projects, hands-on activities etc.

  • Online Sessions + Live Lectures

  • 5 Projects and Assignments

  • Personalised Industry Session

  • Student Support available all day for your convenience (24*7)

  • Software Career Transition Bootcamp for non-tech and new coders

  • No Cost EMI Option

  • 10+ Programming Tools & Languages

  • Capstone Project

  • Direct access with expert to Clear doubts and asking queries 

Who Is This Programme For?

Software Developers, IT Professionals, Engineers, Analysts, Tech Support Professionals, Freshers wanting to kick-start their career in software development

Bachelor’s Degree with 50% or equivalent passing marks. No coding experience required.

Minimum Eligibility
Top Skills You Will Learn

Fundamentals of Data science and Machine Learning, Decision making on data, Data analyst, building and deploying the models.

Job opportunities

Data Scientist, Data Engineer,  Data Analyst, Machine Learning Engineer, AI & ML based app developers

Curriculum

The Data Science and Machine Learning Program curriculum has been carefully crafted by Codersarts team to provide you with the skills & knowledge to apply data science techniques to help you make data-driven decisions. Encompass the most business-relevant technologies, such as Machine Learning, Deep Learning, NLP, Recommendation Systems, and more.

Introduction

1 - 3 Weeks
  • Environment setup of python

  • Setting up machine learning environment (python)

  • Jupiter notebook , anaconda , other local environments

  • Arithmetic operators in Python: Python

  • Strings in Python: Python Basics

  • Lists, Tuples and Dictionaries: Python Basics

  • Working with Numpy

  • Working with pandas

  • Working with Matplotlib

  • Overview of Sklearn

  • Overview of different ML models

Data Exploration and Manipulation

2 - 3 Weeks
  • Data collection - Importing Data in Python, Data Exploration, The Dataset and the Data Dictionary

  • ​​Data preprocessing- Data conversions, Bivarient analysis /variable conversions  -non Usable variables 

  • Outliers

  • EDA - Missing value treatment, Dummy value creation and handling, Correlation Analysis, Test train split, Bias Variance trade-off

  • Feature engineering - feature extraction, catagorical data encoding, one-hot-encoding

Model selection procedures

1 - 3 Weeks
  • Supervised Learning

  • Unsupervised Learning

  • Reinforcement Learning

  • Introduction to overfitting, hyperparameters, cross-validation 

  • Model Selection Techniques

  • Classifications,

  • Clustering

  • Regression

Model Evaluation

2 - 3 Weeks
  • Model Accuracy

  • Precision

  • Recall

  • F1 score

  • Jaccard

  • AUC

  • ROC

  • MSE

  • MAE

Machine Learning Pipeline

1 - 2 Weeks
  • Building project by completing all steps

  • Model accuracy improvement

  • Basic Hyper tuning 

  • Model comparison using standard techniques

  • Preparing model for deployment 

Projects and Hands-on

2 - 4 Weeks
  • Classification on iris dataset

  • Disease prediction (diabetes dataset)

  • Image classification on handwritten datasets

  • Recommendation system

  • Image classification

  • Text classification

  • Sentiment analyzer

  • Facial image classification

Technologies you will learn

  • Numpy

  • Pandas

  • SciPy

  • Matplotlib

  • Scikit-learn

  • EDA

  • Feature engineering

  • Machine Learning

  • Data Science

  • Python Or R

  • Hyper tuning

  • model for deployment

  • Jupiter notebook, Google Colab, AWS Sagemaker

Syllabus

Best-in-class content by leading faculty and industry leaders in the form of videos, cases and projects

Other Related courses

Coming Soon

  • Computer Vision

  • Deep Learning 

  • NLP

  • Classification analysis

  • Regression analysis 

  • Clustering analysis

  • Classification analysis

  • Feature engineering in Python

GET IN TOUCH

We'd love to hear from you
Call now

0120-411-8730

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