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Description

This foundational course provides a high-level overview of essential Data Science areas. A basic understanding of Data Science from business and technology perspectives is provided, along with an overview of common benefits, challenges, and adoption issues.In this course, you will learn the foundations for Data Science and also learn to use Python - a powerful open source tool. You will come across interesting concepts like exploratory data analysis, statistics fundamentals, hypothesis testing, regression & classification modeling techniques and get introduced to machine learning. The course end project and interview prep will make you industry ready. 

Named the sexiest career of the 21st century by none other than the Harvard Business Review, the demand for Data Scientists is rapidly increasing year-on-year. It has been proven that data scientists earn base salaries up to 36% higher than other predictive analytics professionals.  Glassdoor reports that the national average salary for a Data Scientist is $1,39,840 in the United States.

KnowledgeHut’s Data Science Foundation course will helps freshers and seasoned professionals alike to gain a deep understanding of the subject and advance your career.

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What You Will Learn

1. Data Science Tools & Technologies

Get acquainted with various analysis and visualization tools such as matplotlib and seaborn

2. Statistics for Data Science

Understand the behavior of data as you build significant models

3. Python for Data Science

Learn about the various libraries offered by Python to manipulate data

4. Exploratory Data Analysis

Use Python libraries for data preparation and visualizing data

5. Advanced Statistics & Predictive Modeling

ANOVA, Linear Regression using OLS, Logistic Regression using MLE, KNN, Decision Trees

6. Optimize Model Performance

Enhance the model performance using techniques like Feature Engineering and Regularization

7. Dimensionality Reduction

Techniques to find optimum number of components/factors using scree plot, one-eigenvalue criterion

8. Basics of Machine Learning

Learn basics of ML techniques; types of learning and learn about scikit learn library

8. Basics of Machine Learning

Learn basics of ML techniques; types of learning and learn about scikit learn library

1. Data Science Tools & Technologies

Get acquainted with various analysis and visualization tools such as matplotlib and seaborn

2. Statistics for Data Science

Understand the behavior of data as you build significant models

3. Python for Data Science

Learn about the various libraries offered by Python to manipulate data

4. Exploratory Data Analysis

Use Python libraries for data preparation and visualizing data

5. Advanced Statistics & Predictive Modeling

ANOVA, Linear Regression using OLS, Logistic Regression using MLE, KNN, Decision Trees

6. Optimize Model Performance

Enhance the model performance using techniques like Feature Engineering and Regularization

7. Dimensionality Reduction

Techniques to find optimum number of components/factors using scree plot, one-eigenvalue criterion

8. Basics of Machine Learning

Learn basics of ML techniques; types of learning and learn about scikit learn library

1. Data Science Tools & Technologies

Get acquainted with various analysis and visualization tools such as matplotlib and seaborn

Prerequisites
  • Elementary programming knowledge
  • Familiarity with statistics

Who should Attend?

Those interested in data science who want to learn essential data science skills
Those looking for a more robust, structured data science learning program
Data Analysts, Economists, or Researchers working with large datasets
Software or Data Engineers interested in learning basics of quantitative analysis

KnowledgeHut Experience

Instructor-led Live Classroom

Interact with instructors in real-time— listen, learn, question and apply. Our instructors are industry experts and deliver hands-on learning.

Curriculum Designed by Experts

Our courseware is always current and updated with the latest tech advancements. Stay globally relevant and empower yourself with the training.

Learn through Doing

Learn theory backed by practical case studies, exercises and coding practice. Get skills and knowledge that can be effectively applied.

Mentored by Industry Leaders

Learn from the best in the field. Our mentors are all experienced professionals in the fields they teach.

Advance from the Basics

Learn concepts from scratch, and advance your learning through step-by-step guidance on tools and techniques.

Code Reviews by Professionals

Get reviews and feedback on your final projects from professional developers.