Data Science Quick Start: An Introductory Crash Course for Technical Professionals

By Sarmista Thalapaneni, Chaitanya Krishna Kasaraneni, Srikar Kashyap Pulipaka

A fast, practical path into the data science life cycle for technical professionals.

Starting with data collection and management, you learn hands-on data cleaning and wrangling, exploratory data analysis and visualization, and statistical modeling and inference that lead naturally into supervised and unsupervised learning. Clear guidance on model evaluation metrics, feature engineering, and time series forecasting helps you match methods to workloads with reasons grounded in practice.

The book then extends into deep learning and natural language processing, covering neural network foundations alongside applied text workflows such as sentiment analysis, named entity recognition, topic modeling, and transformer techniques. Cloud-oriented deployment concepts, reproducible workflows, and governance are treated vendor-neutral. Dedicated coverage of data ethics, privacy, fairness, and accountability ensures responsible practice. Business analytics use cases, tool fundamentals, portfolio-building advice, and future trends round out a graduate-level yet accessible crash course aimed at quick adoption and durable skills.

What You Will Learn

Execute the complete data science life cycle from collection to deploymentConduct exploratory data analysis and create effective visualizationsApply statistical modeling and inference to real analytical problemsBuild supervised and unsupervised learning workflows with rigorous evaluationDesign and train deep learning models for vision and sequence dataImplement NLP pipelines including sentiment analysis, NER, topic modeling, and transformer methodsDevelop time series forecasting with seasonality and validation strategiesApply reproducible workflows and deployment choices for cloud environmentsIntegrate ethical AI, privacy, fairness, and governance into projects

Who This Book Is For

Technical professionals with basic coding and quantitative fundamentals who need a concise, hands-on ramp into the data science life cycle.

• Format: Paperback
• Language: English
• ISBN: B0HD6J18ZG
• ISBN13: 9798868833076
• Release Date: January 2027
• Publisher: Apress