About the course:
This Data Scientist course aims to accelerate your career in Data Science and provides you with world-class training and skills required to become successful in this field. The Data Scientist course offers extensive training on the most in-demand Data Science and Machine Learning skills with hands-on exposure to key tools and technologies including Python, Web Scraping, NLP, Data Visualization, Statistics, and concepts of Machine Learning and Deep Learning.
Skills you will learn:
Python Programming, Statistics for Machine Learning, understanding of data structure and data manipulation, machine learning model building, deep learning
The following topics will be covered as part of Data Science Mentorship Program.
Introduction to the course
Introduction to Data Science
Introduction to Analytics
Design Thinking and Problem Statement
Mini Project 1
Master Python Programming
Python Variables: int, float, string, bool, complex
Python Collections: List, Tuple, Dictionary, Set, Frozenset
Mini Project 3
Functions and Methods
Class & Objects
Mini Project 4
Working with CSV and Text files
Project 2: Using Python concepts
Data and Types
Central Tendency: Mean, Median, Mode
Deviation: Range, Variance, Standard Deviation
BoxPlot and its importance
Mini Project 5
Frequency distribution and its importance
Mini Project 6
Scatter Plots and its importance
Mini Project 7
Mini Project 8
Matplotlib: basic plots and advanced plots
Mini Project 9
Seaborn: basic plots and advanced plots
Mini Project 10
NLP: N-gram models of language
Project 3: NLP
Project 4: Web scraping and visualization
Discrete Probability Distribution: Binomial Distribution, Poisson
Continuous Probability Distribution: Normal, t distribution, Exponential
Mini Project 11
Data Science Methodology
Types of learning
Regression: Simple linear, multiple linear, ridge, lasso, decision tree, random forest
Classification: svm, decision tree, random forest, naïve bayes, bagging, boosting
Clustering: K means, Hierarchical
Association: Market Basket Analysis
Mini Project 12
Neural Network – ANN, CNN, RNN
Long Short-term memory (LSTM)
Restricted Boltzman Machine (RBM)
Duration & Timings :
Total Hours – 100 Hours.
Duration – 12 Weeks.
Training Type: Online Live Interactive Session.
Access to Class Recordings.
Days: MON – THU (4 Days/ Week)
Start Date :Monday, January 2, 2023.
Time – 8:30 PM to 10:30 PM (EST)