KaaShiv's Training Program will provide you with in-depth knowledge in Data Science

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Most popular course on Data Science trusted by over 50,000 students! Built with years of experience by industry experts and gives you a complete package of video lectures, practice problems, quizzes. Start Today!

900 ~~900~~ 40%
off

Available for 5 Days to

Data Science Internship excellent to learn

Get Job from Top Companies with this Internship

Average Salary

Rs.5,00,000 - 8,00,000 / Year

What is Data Science?

Course Content

5 Days

Topic | Text Material | Image content | Video content | Quiz |
---|---|---|---|---|

Data Science Introduction | - | |||

Data Science Environment Setup | - | |||

Data Science - Python - Introduction to Python | - | |||

Data Science - Python - Introduction to Python IDLE | - | |||

Data Science - Python - Basic Syntax Rules | - | |||

Complete reference on Data Science | - |

10 Days

Topic | Text Material | Image content | Video content | Quiz |
---|---|---|---|---|

Python Data Operations | - | |||

Python Data Cleansing | - | |||

Python Processing CSV Data | - | |||

Python Processing JSON Data | - | |||

Python Processing XLS Data | - | |||

Python Relational Databases | - | |||

Python NoSQL Databases | - | |||

Python Date and Time | - | |||

Python Data Wrangling | - | |||

Python Data Aggregation | - | |||

Python Reading HTML Pages | - | |||

Python Processing Unstructued Data | - | |||

Python Word Tokenization | - | |||

Python Stemming and Lemmatization | - |

15 Days

Topic | Text Material | Image content | Video content | Quiz |
---|---|---|---|---|

Python Chart Properties | - | |||

Python Chart Styling | - | |||

Python Box Plots | - | |||

Python Heat Maps | - | |||

Python Scatter Plots | - | |||

Python Bubble Charts | - | |||

Python 3D Charts | - | |||

Python Times Series | - | |||

Python Graph Data | - |

1 Month

Topic | Text Material | Image content | Video content | Quiz |
---|---|---|---|---|

Python Measuring Central Tendency | - | |||

Python Measuring Variance | - | |||

Python Normal Distribution | - | |||

Python Binomial Distribution | - | |||

Python Poisson Distribution | - | |||

Python Bernoulli Distribution | - | |||

Python P Value | - | |||

Python Correlation | - | |||

Python Chi Square Test | - |

2 Months / 6 Weeks

Topic | Text Material | Image content | Video content | Quiz |
---|---|---|---|---|

Data Science - Python - Numbers and Math Functions | - | |||

Data Science - Python - Operators | - | |||

Data Science - Python - Variables | - | |||

Data Science - Python - Modules and functions | - | |||

Data Science - Python - Input and Output | - | |||

Data Science - Python - String functions | - | |||

Data Science - The Data Analysis Process | - | |||

Data Science - Python - The Interpreter | - | |||

Data Science - Numpy Installation | - | |||

Data Science - Numpy - Basic Opeartions : | - | |||

Data Science - Numpy - Indexing, Slicing, and Iterating | - | |||

Data Science - Numpy - Conditions & Boolean Arrays | - | |||

Data Science - Numpy - Array Manipulation | - | |||

Data Science - Numpy - General/Advanced concepts | - | |||

Data Science - Numpy - Structured Arrays | - | |||

Data Science - Read Write Array Data on Files | - | |||

Data Science - Pandas - Data Structures | - | |||

Data Science - Pandas - Operations and Mathematical Functions | - | |||

Data Science - Pandas - Series as Dictionaries | - | |||

Data Science - Pandas - DataFrame from Nested dict | - | |||

Data Science - Pandas - Operations between Data Structures | - | |||

Data Science - Pandas - Function Application and Mapping | - | |||

Data Science - Pandas - Sorting and Ranking | - | |||

Data Science - Pandas - Correlation and Covariance | - | |||

Data Science - Pandas - Hierarchical Indexing and Leveling | - | |||

Data science - pandas - Read and Write file | - | |||

Data Science - Pandas - Reading and Writing HTML Files | - | |||

Data Science - Pandas -Reading Data from XML | - | |||

Data Science - Pandas -Read Write on Excel | - | |||

Data Science - Pandas - JSON Data | - | |||

Data Science - Pandas - Load or Write Data with SQLite3 | - | |||

Data Science - Pandas Adv - Data Preparation | - | |||

Data Science - Pandas - Data Transformation | - | |||

Data Sciecne - Pandas - Discretization and Binning | - | |||

Data Science - Pandas - String Manipulation | - | |||

Data Science - Pandas - Data Aggregation | - | |||

Data Science - Pandas - Group Iteration | - | |||

Data Science - Pandas - Advanced Data Aggregation | - | |||

Data Science - Pandas - Data Visualization with matplotlib | - | |||

Data Science - Adding Further Elements to the Chart | - | |||

Data Science - Saving Your Charts | - |

3 Months

Topic | Text Material | Image content | Video content | Quiz |
---|---|---|---|---|

Python Geographical Data | - | |||

Python Linear Regression | - | |||

Data Science in Big Data World | - | |||

Data Science Process | - | |||

Big data ecosystem and Data Science | - | |||

Applications for Machine Learning in Data Science | - | |||

Python tools used in machine learning | - | |||

Modeling Process | - | |||

Data Science Algorithms | - | |||

Data Science Programming Languages | - | |||

Importance of SQL in Data Science | - | |||

Mathematics & Statistics for Data Science | - | |||

Data Science Applications | - | |||

Future of Data Science | - | |||

SAS for Data Science | - | |||

Data Sciecne - Pandas - Permutation | - | |||

Data Science - Histogram | - | |||

Data Science - Bar Chart | - | |||

Data Science - Pie Charts | - | |||

Data Science - Bar Chart 3D | - | |||

Data Science - Multi-Panel Plots | - |

6 Months

Topic | Text Material | Image content | Video content | Quiz |
---|---|---|---|---|

Python Pandas | - | |||

Python Numpy | - | |||

Python Scipy | - | |||

Python Matplotlib | - | |||

Need for Data Science | - | |||

Data Science Jobs | - | |||

Components of Data Science | - | |||

Data Science Life Cycle | - | |||

Applications of Data Science | - | |||

Data Science - pandas - Data Analysis Lib | - | |||

Data Science - Machine Learning with scikit-learn | - | |||

Data Science - K-Nearest Neighbors Classifier | - | |||

Data Science - Linear Regression - The Least Square Regression | - | |||

Data Science - Support Vector Machines (SVMs) | - | |||

Data Science - Support Vector Regression (SVR) | - |

Data is the new Oil. This statement shows how every modern IT system is driven by capturing, storing and analysing data for various needs. Be it about making decision for business, forecasting weather, studying protein structures in biology or designing a marketing campaign. All of these scenarios involve a multidisciplinary approach of using mathematical models, statistics, graphs, databases and of course the business or scientific logic behind the data analysis. So we need a programming language which can cater to all these diverse needs of data science. Python shines bright as one such language as it has numerous libraries and built in features which makes it easy to tackle the needs of Data science.

In this internship we will cover these the various techniques used in data science using the Python programming language.

This internship is designed for Computer Science graduates as well as Software Professionals who are willing to learn data science in simple and easy steps using Python as a programming language.

Before proceeding with this internship, you should have a basic knowledge of writing code in Python programming language, using any python IDE and execution of Python programs. If you are completely new to python then please refer our python get a sound understanding of the language.

Earn official recognition for your work, and share your success with friends, colleagues, and employers.

S

Surya Maharajan

S

Sundar Manikandan

A

A Anand

We have a lifetime 24x7 online support team to resolve all your technical queries, through a ticket based tracking system.

Successfully complete your final course project and Kaashiv will certify you as a Data Science Expert.

We have a community forum for all our learners that further facilitates learning through peer interaction and knowledge