Course
Data Science
Provide Data Science Training
300 trained in last 3 years
Real time expert trainers
Indutry oriented training with corporate casestudies
Free Mock interviews
About Data Science Course
Data Science is a complete business suite that empowers different opportunities in many streams which helps us in making better choices for some business issues. Data Science is a course of tracking down the best fit model for the data until you get the fulfilled exactness. Picking an algorithm relies upon many elements which incorporates, understanding the business issue, characterizing your target capacity and understanding the data. Data science includes plenty of disciplines and ability areas to deliver an all-encompassing, exhaustive and refined investigation of raw data. Logical applications and data researchers would then be able to audit the outcomes to uncover designs and empower business pioneers to draw educated experiences.
Data Science Course Curriculum
- What is Data Science? Why we need it?
- Applications of Data Science
- Data Science Life Cycle
- Understanding Business Requirement
- Data Types
- Data Collection Sources
- Data Collection Methods
- Web Scraping
- Data Cleaning & Preprocessing techniques
- Data Visualization using various plots
- Line Plot
- Bar Plot
- Histogram
- Pie Chart
- Scatter Plot
- Box Plot
- Heat Map, etc
- Handling Missing Data
- Exploratory Data Analysis (EDA) with Use case
- Types of Data & Scales of Measurements
- Measures of Central Tendency
- Measures of Variability
- Skewness and Kurtosis
- Population & Sample
- Normal & Sampling Distributions
- Central Limit Theorem and Confidence Interval
- Hypothesis Testing
- ANOVA
- Simple Linear Regression and Correlation
- Nonparametric Methods and Chi-Square Tests
- Dimensionality Reduction
- Cluster Analysis
- Model performance Metrics (Performance Evaluation)
- Combining Methods: Ensembles and Uplifting Modeling
- Associate Rules and Collaborative Filtering
- Types of Forecasting
- Trend Analysis
- Seasonality and Cyclical Behavior
- Stationarity
- AR, MA, ARIMA Models
- Smoothing Methods
- Multiple Linear Regression
- k-Nearest Neighbors (kNN)
- Naïve Bayes Classifier
- Regression and Classification Trees
- Logistic Regression
- Neural Nets
- Discriminant Analysis
- Support Vector Machines
- Introduction to Text analytics and NLP
- Applications of NLP
- Regular Expressions
- Stemming & Lemmatization
- Bag of Words
- POS tagging
- DTM
- TF-IDF
- NER
- Sentiment Analysis with Use case
- Python
- R
- Tableau
- Excel
Data Science Course Highlights
- Online live training by a trained instructor
- Training by real-time professionals
- Real-time scenarios
- Study Material
- Notes
- Test Projects
- Practice Assignments
- Mock Interviews
Software Trainings
Job Supports
Useful Links
© 2026 TeachingHills Training Center | All Rights Reserved
