We focus on the essentials of Python Programming Language, Statistics, and Machine Learning yet additionally causes one to increase ability in applied Data Science at scale utilizing Python. The preparation is a bit by bit manual for Python and Data Science with broad hands on. The course is stuffed with a few movement issues and tasks and situations that help you pick up pragmatic involvement with tending to prescient modeling issues that would either require Machine Learning utilizing Python.
DATA SCIENCE COURSE CURRICULUM
Topics
- Introduction To Data Science
- Industry Applications
- Terminologies
Topics
- Anaconda – Python Distribution Installation And Setup
- Jupyter Notebook
- Python Basics
- Data Structures
- Control Statements
Topics
- R Installation And Setup
- R Studio Basics
- R Data Structures
- Control Statements
- Data Science Packages
Topics
- Essential Mathematics
- Linear Algebra
- Linear Transformation
- Types Of Matrices, Matrix Properties, And Operations Probability And Calculus
Topics
- Statistics Introduction
- Terminologies
- Inferential Statistics
- Exploratory Analysis
- Distributions
- Central Limit Theorem
- Hypothesis Testing
- Correlation, And Regression
Topics
- Numpy Array Functions
- Data Munging With Pandas
- Imputation
- Outlier Analysis
Topics
- Visualization Basics
- Matplotlib Introduction
- Basic Plots
- Customizing Plots
- Sub-Plots
- Statistical Plots
- Seaborn Package Introduction
Topics
- Machine Learning Introduction
- Ml Core Concepts
- Unsupervised And Supervised Learning
- Clustering With K-Means
- Linear Regression
- Logistic Regression
- K-Nearest Neighbor
Topics
- 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
Topics
- Relational Database Management Systems Basics
- Sql Introduction
- Connection To Sql Databases
- Fetching Data With Select
- Where Condition
- Sql Joins
- Sql Crud Operations
Topics
- Deep Learning Introduction
- Tensorflow And Keras
- Convolution Neural Network Basics
- End To End Image Classification Of Cats And Dogs Using The Tensorflow-Keras Platform.
Topics
- Visual Analytics Basics
- Tableau Introduction
- Connecting To Datasource
- Dimensions Vs Measures
- Basic Plots
- Compound Plots
- Forecasting
- Publishing
Topics
- Ml Deployment Strategies
- Flask Introduction
- Packing Training Ml Model
- Deploying It On Flask As Api
Topics
- Data Science Project Management Method
- Business Case Risk
- Limitation Of Machine Learning
- Project Pitfalls.
Topics
- Hadoop Concepts
- Spark Big Data for Data Science Processing
- Handling Big Data in Machine Learning Pipeline.
DATA SCIENCE COURSE DESCRIPTION
Best Data Science course in Bangalore is provided by Achievers IT training institution. Our training program is especially for Students, Working Professionals & Business Owners. We teach you all programming languages from scratch. our expert faculty create the best possible data science course which would deliver the most value to you
- Automatically download and investigate Data
- Learn methods to manage various sorts of data – ordinal, absolute, encoding
- Learn data analysis
- Utilizing python notepads, ace the specialty of introducing bit by bit data examination
- Gain understanding into the ‘Jobs’ played by a Machine Learning Engineer
- Portray Machine Learning
- Work with constant data
- Learn instruments and methods for prescient displaying
- Analysis Machine Learning calculations and their execution
- Approve Machine Learning calculations
- Clarify Time Series and its connected ideas
- Perform Text Mining and Sentimental investigation
- Gain the ability to deal with business in future, living the present
- Automatically download and investigate Data
- Learn methods to manage various sorts of data – ordinal, absolute, encoding
- Learn data analysis
- Utilizing python notepads, ace the specialty of introducing bit by bit data examination
- Gain understanding into the ‘Jobs’ played by a Machine Learning Engineer
- Portray Machine Learning
- Work with constant data
- Learn instruments and methods for prescient displaying
- Analysis Machine Learning calculations and their execution
- Approve Machine Learning calculations
- Clarify Time Series and its connected ideas
- Perform Text Mining and Sentimental investigation
- Gain the ability to deal with business in future, living the present
- software engineers, Developers, Technical Leads, Architects
- developer seeking to be an ‘AI Engineer’
- Examination Managers who are driving a group of experts
- ‘Python’ experts who need to plan programmed prescient models
- No prior knowledge. You will start from the basics.
- A willingness to learn and practice.
- Microsoft Excel
DATA SCIENCE COURSE PROJECT
- A system with an Intel i3 processor or above
- A minimum of 3GB RAM (4GB or above recommended for faster processing)
- Operating system: 32bit or 64 bits
You will do your assignments/case studies using Jupyter Notebook that is already installed on your Cloud LAB environment (access it from a browser). The access credentials are available on your LMS. Should you have any queries, the 24*7 Support Team will promptly assist you.