Become a Data Science Expert

Master the skills required for data science, including data analysis, machine learning, and statistical modeling. Learn to work with tools like Python, R, and SQL to extract valuable insights from large datasets and solve complex problems.

Data Science Course

Description

Embark on a transformative journey with Urbancode's Data Science Certification Program. Crafted by seasoned experts, this online course delves into foundational and advanced data science concepts. From mastering statistical analysis to machine learning algorithms, participants gain hands-on experience, empowering them with the skills needed to excel in the dynamic field of data science.

Why should you choose this course?

Empowering careers
Diverse career paths in data science, including roles such as data analyst, machine learning engineer, data scientist, and more.

Industry Relevance
Familiarize yourself with in-demand tool Python and popular libraries like NLTK, SpaCy and Scikit-Learn.

Data-Driven Decision Making
Learn to manipulate and preprocess data effectively, a fundamental skill in the data science workflow.

High Demand
Acquire the highly sought-after skills in data analysis, machine learning, and statistical modeling that are in high demand across industries.

This course includes

  • 60 hrs Instructor-Led Training
  • 30 hrs Project & Exercises
  • Mentor Support
  • Placement Assistance
  • 3 downloadable resources

Course content

Introduction to Statistical Analysis & Concepts

  • Introduction to Probability Theory
  • Data Analysis: Measures of Central Tendency & Dispersion
  • Introduction to Distributions (Normal, Poisson, Binomial)
  • Hypothesis Testing (Null & Alternate Hypothesis)

Linear Regression

  • Basics of OLS Regression
  • Assumptions & Features of Linear Regression
  • Introduction to Gradient Descent & its loss function
  • Gradient Descent ve Linear Regression
  • Other Gradient Descent Algorithms
  • Other Regression Algorithms: Ridge & Lasso Regression

Classification

  • Logistic Regression
  • Naive Bayes & Conditional Probability
  • K Nearest Neighbour
  • Bagging & Boosting Algorithms: Decision Trees, Random Forest, XGBoost

Unsupervised Learning

  • Introduction to Clustering
  • K Means Clustering
  • Hierarchical Clustering
  • DBScan Algorithm

Text Mining

  • Intro to Text Mining & Information Retrieval
  • Parts of Speech Tagging
  • Sentiment Analysis
  • Recommender Systems

Advanced AI & ML Algorithms

  • Introduction to Deep Learning & Neural Networks
  • Convoluted Neural Networks & Recurrent Neural Networks
  • Introduction to Reinforcement Learning
  • Basics of Gen AI

Introduction to Analytics Industry

  • Opportunities in Analytics & AI (India & Abroad)
  • Companies and Job Profiles in Analytics
  • Intro to Kaggle & GitHub
  • New trends in Analytics
  • Tips & Tricks for successful transition into Analytics

Live Project

  • Project Discussion
  • Problem Statement & Solution Design
  • Doubts resolution
  • Best Practices & Recommendations

Testimonials

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