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Instructor Name

Saurabh Sharma

Category

Data Science

Reviews

( 4.8 )

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Course Description

From asking the appropriate questions to generating conclusions and reporting results, this specialization covers the ideas and tools you'll need across the data science pipeline. In the Capstone Project, you'll put your newfound abilities to use by creating a data product based on real-world data. Students will have a portfolio at the end of the course that demonstrates their knowledge of the content.

This Specialization will teach you about data science and the jobs that data scientists perform. You'll study how data science may be used in a variety of disciplines and how data analysis can assist you in making data-driven decisions. You'll discover that you may get a head start in the industry without any prior understanding of computer science or programming languages. This Specialization will provide you with the foundation you'll need to pursue more advanced studies to further your career objectives. You'll learn about big data, statistical analysis, and relational databases, as well as Jupyter Notebooks, RStudio, GitHub, and SQL, among other open-source tools and data science applications used by data scientists. You'll go through hands-on labs and projects to master the methods behind solving data science issues and apply what you've learned to real-world data sets.

Course Curriculum

1 Installation Introduction to Python
2 Loops
3 Conditional statements
4 Functions
5 Lists
6 Dictionary
1 Numpy library
2 Numpy library Part-II
3 Pandas
4 Pandas Part-II
5 Matplotlib
6 Seaborn
1 Intoduction to EDA
2 One hot encoding, Finding outliers
1 Introduction to Data Science
2 Linear regression
3 Logistic Regression
4 Logistic Regression Part-II
5 Model Evaluation Methods
1 Statistics
00:56:29
2 Statistics
01:09:45
3 Advanced Supervised Machine Learning algorithms - Decision Trees
01:24:50
4 Random Forest
01:17:00
5 Cross Validation
01:10:00
6 Hyper Parameter Tuning
00:56:00
7 Support Vector Machines [part1 ]
01:19:00
8 Support Vector machines [ part2 ]
01:11:00
9 K-nearest neighbor algorithms
01:29:43
1 UnSupervised Machine Learning algorithms - Principal Componenet Analysis (PCA)
01:25:12
2 K-means Clustering
01:16:55
3 Association Rule Mining
01:25:12
4 Natural language Processing
01:07:27
1 SQL [ Part 1 ]
01:07:10
2 SQL [ Part 2 ]
01:04:59
3 SQL [ Part 3 ]
01:13:19
4 Intro to Neural Network
01:13:21
5 Neural Network
00:57:50
6 Deep Learning Concepts [ Part 1 ]
01:23:53
7 Deep Learning Concepts [ Part 2 ]
01:18:23
8 Deep Learning Concepts [ Part 3 ]
01:03:36
9 Deep Learning Concepts [ Part 4 ]
01:19:26
1 Working on Projects [ Part 2 ]
00:51:11
2 Working on Projects [ Part 1 ]
00:36:57

Instructor

Saurabh Sharma

After completing his graduation in IT, Saurabh did his MBA from Amity Business School. Being a certified SAP consultant with domain experience of close to 13 years, Saurabh have a keen eye for data anomalies and visualization techniques.

4.8 Rating
5 Reviews
492 Students
16 Courses

Meghna Shrivastav

Ms. Meghna Shrivastav has completed her Bachelor’s Of Technology in Computer Science. During her curriculum she has earned various certifications dealing with analytics and critical thinking in communications.

Karamjeet Gulati

Mr. karamjeet is B.Tech from SRM University, with strong problem solving ability and good grasp in data science and machine learning.

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[6-months] Data Science Course

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