##### Data Science Training

Day | Session | Topics | Exam |
---|---|---|---|

01 | Statistics for Data Science Part 1 | ||

02 | Statistics for Data Science Part 2 | 10 min 10 questions | |

03 | Statistics for Data Science Part 3 | 10 min 10 questions | |

04 | Statistics for Data Science Part 4 | 10 min 10 questions | |

05 | Statistics for Data Science Part 5 | 10 min 10 questions |

Day | Session | Topics | Exam |
---|---|---|---|

01 | Python for Data Science Part 1 | ||

02 | Python for Data Science Part 2 | 10 min 10 questions | |

03 | Python for Data Science Part 3 | 10 min 10 questions | |

04 | Python for Data Science Part 4 | 10 min 10 questions |

Day | Session | Topics | Exam |
---|---|---|---|

01 | Exploration Data Analysis with Python | ||

02 | Visualization Part 1 | 10 min 10 questions | |

03 | Visualization Part 2 | 10 min 10 questions | |

04 | Data Pre-processing Part 1 | 10 min 10 questions | |

05 | Data Pre-processing Part 2 | 10 min 10 questions |

Day | Session | Topics | Exam |
---|---|---|---|

01 | Introduction to ML | ||

02 | Regression Analysis | 10 min 10 questions | |

03 | Linear Regression | 10 min 10 questions | |

04 | Project in Linear Regression | 10 min 10 questions | |

05 | Logistic Regression | 10 min 10 questions | |

06 | Project in Logistic Regression | 10 min 10 questions | |

07 | Overfitting and Underfitting | 10 min 10 questions | |

08 | KNN | 10 min 10 questions | |

09 | Project in KNN | 10 min 10 questions | |

10 | Decision Tree | 10 min 10 questions | |

11 | Project using DT | 10 min 10 questions | |

12 | k-fold cross validation | 10 min 10 questions | |

13 | SVM | 10 min 10 questions | |

14 | Project using SVM | 10 min 10 questions | |

15 | Ensemble Techniques and Random Forest | 10 min 10 questions | |

16 | Project using Random Forest | 10 min 10 questions |

##### Natural Language Processing

Day | Session | Topics | Exam |
---|---|---|---|

01 | NLP Introduction | ||

02 | Introducing NLP concepts and Techniques | 10 min 10 questions | |

03 | NLP Libraries Introduction | 10 min 10 questions | |

04 | Text Pre-processing using spaCy | 10 min 10 questions | |

05 | Parts of Speech Tagging and Named Entity Recognition | 10 min 10 questions | |

06 | Feature Extraction Techniques | 10 min 10 questions | |

07 | Text classification Project | 10 min 10 questions | |

08 | Semantics and sentiment analysis Project | 10 min 10 questions | |

09 | Topic Modelling | 10 min 10 questions | |

10 | Deep Learning for NLP | 10 min 10 questions | |

11 | RNN and LSTM | 10 min 10 questions | |

12 | Project- Text generation | 10 min 10 questions | |

13 | Chat Bot Implementation | 10 min 10 questions | |

14 | Transformers | 10 min 10 questions | |

15 | Introduction to pre-trained models for NLP tasks | 10 min 10 questions | |

16 | Project using Random Forest | 10 min 10 questions |

## What We Provide

##### Mock Interviews

Job Specific Mock Interview practices to improve the chance of landing in your Data Science dream job.

##### Guided Mentorship

Get a chance to have one on one mentorship session from top industry experts.

##### Study Material

Ask for Study Material related to Data Science, AI & ML designed for specific industry defined roles.

## Assessments

##### Machine Learning

##### NLP

##### Computer Vision

## Get in Touch

### Bengaluru Karnataka.

India

### +91 7905809152

Mon to Fri 7 PM to 10 PM. Sat & Sun 9 AM to 8 PM

### [email protected]

Send us your query anytime!

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##### Schedule Mock Interview

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