Data Science with Python Training Overview
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Data Science with Python Classroom and Online Training provides you to master the fundamentals of Data science and analytics techniques using Python. Data Science with Python Online Training gives you the in-depth knowledge of Python Data Science packages like NumPy, Matplotlib, Pandas, SciPy, and concepts including deep learning algorithms, evaluation of machine learning models, data visualization, and statistical data analysis techniques. Knowledge on Python is required for Data Science training. Data Science with Python training course, you will learn from industry experts with real-time projects to kick-start your career.
Objective of Data Science with Python Training Classes
By the End of the Data Science with Python Training:
- You will have an idea of what Python is and the basics of Python
- You will have the knowledge of creating generic python scripts, debugging, and execute
- You will learn about data visualization
- You will have an understanding of Data Manipulation.
- Knowledge about the concept of Machine Learning and its types, Supervised Learning Techniques and their implementation, developing of LDA model, Unsupervised Learning and the various types of clustering, developing of the smart learning algorithm
- Expertise on Time Series Analysis to forecast dependent variables based on time
- You will learn how to convert weaker algorithms into stronger ones
Data Science with Python Training is useful for Programmers, Developers, Technical Leads, and Architects for an aspiring career in Data Science
Data Science with Python Course Curriculum
- Overview of Python
- The Companies using Python
- Different Applications where Python is used
- Discuss Python Scripts on UNIX/Windows
- Values, Types, Variables
- Operands and Expressions
- Conditional Statements
- Command Line Arguments
- Writing to the screen
- Python files I/O Functions
- Strings and related operations
- Tuples and related operations
- Lists and related operations
- Dictionaries and related operations
- Sets and related operations
- Functions and their Parameters
- Global Variables
- Variable Scope and Returning Values
- Lambda Functions
- Object-Oriented Concepts
- Standard Libraries
- Modules Used in Python
- The Import Statements
- Module Search Path
- Package Installation Ways
- Errors and Exception Handling
- Handling Multiple Exceptions
- NumPy - arrays
- Operations on arrays
- Indexing slicing and iterating
- Reading and writing arrays on files
- Pandas - data structures & index operations
- Read and Write data from Excel/CSV formats into Pandas
- matplotlib library
- Grids, axes, plots
- Markers, colours, fonts, and styling
- Types of plots - bar graphs, pie charts, histograms
- Contour plots
- Basic Functionalities of a Data Object
- Merging of Data objects
- Concatenation of Data Objects
- Types of Joins on Data Objects
- Exploring a Dataset
- Analyzing a Dataset
- Python Revision (NumPy, Pandas, SciPy learn, matplotlib)
- What is Machine Learning?
- Machine Learning Use-Cases
- Machine Learning Process Flow
- Machine Learning Categories
- Linear Regression
- Gradient Descent
- What are Classification and its use cases?
- What is Decision Tree?
- Algorithm for Decision Tree Induction
- Creating a Perfect Decision Tree
- Confusion Matrix
- What is the Random Forest?
- Introduction to Dimensionality
- Why Dimensionality Reduction
- Factor Analysis
- Scaling dimensional model
- What is Naïve Bayes?
- How Naïve Bayes works?
- Implementing Naïve Bayes Classifier
- What is Support Vector Machine?
- Illustrate how Support Vector Machine works?
- Hyperparameter Optimization
- Grid Search vs Random Search
- Implementation of Support Vector Machine for Classification
- What is Clustering & its Use Cases?
- What is K-means Clustering?
- How does the K-means algorithm work?
- How to do optimal clustering
- What is C-means Clustering?
- What is Hierarchical Clustering?
- How Hierarchical Clustering works?
- What are Association Rules?
- Association Rule Parameters
- Calculating Association Rule Parameters
- Recommendation Engines
- How does Recommendation Engines work?
- Collaborative Filtering
- Content-Based Filtering
- What is Reinforcement Learning
- Why Reinforcement Learning
- Elements of Reinforcement Learning
- Exploration vs Exploitation dilemma
- Epsilon Greedy Algorithm
- Markov Decision Process (MDP)
- Q values and V values
- Q – Learning
- α values
- What is Time Series Analysis?
- Importance of TSA
- Components of TSA
- White Noise
- AR model
- MA model
- ARMA model
- ARIMA model
- ACF & PACF
- What is the Model Selection?
- The need for Model Selection
- What is Boosting?
- How Boosting Algorithms work?
- Types of Boosting Algorithms
- Adaptive Boosting
CA Software Technologies (CAST) provides you with complete Data Science with Python classroom, corporate, online training, and certification program with real-time projects. The course contents are prepared by professional trainers to have a real-time experience. CA Software Technologies the leading training institute helps you with job support for India and abroad. The course content can be customized according to the preferences of the students.