Data Science Training Course
Certified by leading global brands
- Experienced instructors with industry expertise
- Access to official guides and materials
- Covers all exam topics thoroughly
- Flexible study at your own pace
- Support for exam service
- Anytime access to study resources
What you'll learn
This Data Science course by Simplilearn is idealfor beginners,offering a comprehensive 7-hourcurriculum.lt covers vital topics like Python librariesstatistical analysis,and machine learning. With a 90.day access period and a completion certificate, it's avaluable resource for those aspiring to kickstart theirData Science journey.
Training Course Outline
Introduction to Data Science
1.1 Introduction Datascience
2.1 Data Science In Minutes
3.1 What is Data Science
4.1 Top Python Libraries
5.1 Linear Regression Analysis
6.1 Logistic Regression
7.1 Confusion Matrix
8.1 Decision Tree in Machine Learnin
9.1 Random Forest 10.Support Vector Machine
10.1 Support Vector Machine
11.1 K Means Clustering
12.1 Dimensionality Reduction
13.1 How To Become A Data Scientist In 2025
14.1 Data Science Jobs Skills Salary
15.1 Data Science Engineer Resume
16.1 Data Science Interview Questions
Training Options
Self Paced Learning
- Lifelong access to high-quality content
- Curated by industry experts
- Customized learning progress
- 24/7 learner assistance and support
- Follow the latest technology trends
Exam Dump
- 100% Real Exam Practice Tests
- 100% Verified Exam Questions & Answers
- 100% Guarantee Passing Rate
- Average 7 Days to Practice & Pass
Description
The Data Science course by Simplilearn sounds like an excellent opportunity for beginners to kickstart their journey into the field. Covering essential topics such as Python libraries, statistical analysis, and machine learning over a comprehensive 7-hour curriculum is impressive.
Pre-requisites
The course has no specific prerequisites.
Python Datascience PDF Free Download | SPOTO
Python Datascience PDF Free Download | SPOTO
Cours name: python File Type: PDF
Data Science FAQs
What is Data Science?
Data science involves analyzing large datasets to uncover insights that drive business strategies. It fuses techniques from mathematics, statistics, artificial intelligence, and computer engineering to interpret complex data and extract valuable information.
What does a data scientist actually do?
A data scientist dives into vast amounts of data to identify patterns and trends that can inform business decisions. Their work helps organizations refine their strategies, tackle challenges, and improve operational efficiency.
What are the skills required for a data scientist?
- Programming: Proficiency in coding to manipulate and analyze data.
- Statistics and Probability: A strong foundation in statistical methods to validate findings.
- Data Wrangling and Database Management: Expertise in cleaning, managing, and retrieving data.
- Machine Learning and Deep Learning: Knowledge of algorithms to build predictive models.
- Data Visualization: Ability to create visual representations of data to communicate insights effectively.
- Cloud Computing: Familiarity with cloud platforms to manage and scale data resources.
- Interpersonal Skills: Strong communication and collaboration skills to work with diverse teams.
What is the difference between data science and AI?
Data science uses statistical methods, analytical techniques, and technological tools to derive insights from data. In contrast, Artificial Intelligence leverages that data to solve cognitive challenges—such as learning, pattern recognition, and emulating human behavior—thereby pushing the boundaries of automated decision-making.
Is data science a good career?
Absolutely! A career in data science offers a rewarding blend of intellectual challenge and financial benefits. With growing demand, plentiful job opportunities, and competitive salaries, data science stands out as a dynamic and promising field for future growth.