DATA SCIENTIST Training provided by DataMites Institute Training Institute in Bangalore,Bommanahalli
DATA SCIENTIST free videos and free material uploaded by DataMites Institute Training Institute staff .
Data Science Foundation
Introduction To Data Science
Industry Applications
Terminologies
Python Essentials
Anaconda - Python Distribution Installation And Setup
Jupyter Notebook
Python Basics
Data Structures
Control Statements
R Language Essentials
R Installation And Setup
R Studio Basics
R Data Structures
Control Statements
Data Science Package
Maths For Data Science
Essential Mathematics
Linear Algebra
Linear Transformation
Types Of Matrices, Matrix Properties, And Operations Probability
And Calculus
Statistics For Data Science
Statistics Introduction
Terminologies
Inferential Statistics
Harnessing Data
Exploratory Analysis
Distributions
Central Limit Theorem
Hypothesis Testing
Correlation, And Regression
Data Preparation With Pandas
Numpy Array Functions
Data Munging With Pandas
Imputation
Outlier Analysis
Visualization With Python
Visualization Basics
Matplotlib Introduction
Basic Plots
Customizing Plots
Sub-Plots
Statistical Plots
Seaborn Package Introduction
Machine Learning Associate
Machine Learning Introduction
Ml Core Concepts
Unsupervised And Supervised Learning
Clustering With K-Means
Linear Regression
Logistic Regression
K-Nearest Neighbor
Advanced Machine Learning
Bayes Theorem
Naïve Bayes Algorithm For Text Classification,
Decision Tree
Ensemble Methods: Random Forest,
Extra Trees
Svm, Boosting Techniques
Xgboost
Artificial Neural Network
Adv Metrics
Imbalanced Dataset
Grid Search
K-Fold Cross-Validation
dation
Sql For Data Science
Relational Database Management Systems Basics
Sql Introduction
Connection To Sql Databases
Fetching Data With Select
Where Condition
Sql Joins
Sql Crud Operations
Deep Learning – Cnn Basics
Deep Learning Introduction
Tensorflow And Keras
Convolution Neural Network Basics
End To End Image Classification Of Cats And Dogs Using The
Tensorflow-Keras Platform.
Tableau Associate
Visual Analytics Basics
Tableau Introduction
Connecting To Datasource
Dimensions Vs Measures
Basic Plots
Compound Plots
Forecasting
Publishing
Ml Model Deploy- Flask Api
Ml Deployment Strategies
Flask Introduction
Packing Training Ml Model
Deploying It On Flask As Api
Data Science Project Execution
Data Science Project Management Method
Business Case Risk
Limitation Of Machine Learning
Project Pitfalls.
Big Data Foundation
Introduction to Big Data
Hadoop Concepts
Spark Big Data for Data Science Processing
Handling Big Data in Machine Learning Pipeline.
These four facets form four pillars for the data science
field. They are 1. Programing 2. Statistics 3. Machine Learning 4. Business
Knowledge.
The course is mainly focussed on Python for core data
science programming, it also includes R as necessary to enable professionals
working in R.
Statistics are covered as required for a Data Scientist, you
may find a detailed syllabus in syllabus tab.
Machine Learning is the main tool kit for Data Science in
predicting classification or regression.
This course courses all popular ML algorithms as detailed in
the syllabus tab.
This course allows candidates to obtain an in-depth
knowledge by laying a strong foundation and covering all the latest data
science topics.
The increasing demand curve for data science professionals
to manage the large set of data in various organizations providing millions of
job opportunities in global markets.
The knowledge gained through this course along with IABAC™ certificate surely helps you to become a data science professional
Write a public review