20 WEEKS

Data Science Training Course

Instructor: Shiva
Category: Development
Last Update: September, 2024
Review:

Rated 4.00 out of 5
(4.00)

Description

In today's data-driven world, businesses rely on data to make informed decisions, innovate, and stay competitive. As a result, the demand for skilled data scientists continues to grow. At Will Power Technologies, our Data Science Training Course is designed to equip you with the knowledge and skills needed to excel in this dynamic field. Whether you're a beginner or an experienced professional looking to enhance your data science expertise, our program is tailored to meet industry standards and prepare you for real-world challenges.

Data Science combines programming, mathematics, and statistical techniques to analyze and interpret complex data, enabling organizations to extract valuable insights. From predicting trends to automating processes, data science plays a pivotal role in various industries, including finance, healthcare, and technology.

At Will Power Technologies, we understand the evolving nature of data science and have developed a curriculum that covers the latest tools, techniques, and methodologies. Our program offers hands-on experience with real-world projects, ensuring that you are well-prepared to enter the job market as a skilled data scientist.

Key Highlights

Our Data Science Training Course is designed to provide a comprehensive learning experience that covers the fundamentals and advanced topics of data science. Aligned with industry certifications, this course ensures that you gain the most sought-after skills to succeed in the field.

Comprehensive Data Science Fundamentals
Real-World Project Experience

Collaborative Learning Environment
Industry-Relevant Case Studies

Certification

It is designed to validate the knowledge, skills, and competencies of individuals in a specific area of study or professional field. The certification program is meticulously designed to ensure that candidates have acquired a comprehensive understanding of the subject matter. It encompasses both theoretical knowledge and practical application, allowing candidates to demonstrate their expertise in real-world scenarios.

The Course Curriculam

Python for machine learning

Introduction to Python
Different Applications where Python is Used
Fundamentals of Python Programming
Values, Types, Variables
Conditional Statements
The Companies using Python
Operations and Expressions
Loops
Demonstrating Conditional Statements
Demonstrating Loops
Packages Installation
Different Applications where Python is Used
Conditional Statements
Values, Types, Variables
Conditional Statements
Python Functions Practice
NumPy Library - Creating NumPy Array
Bar Graph, a Pie Chart to Show Information
Pandas Library - Creating Series and Data
Basic Functionalities of a Data Object
Concatenation of Data Objects
Exploring a Dataset
Merging of Data Objects
Aggregation
Analyzing a Dataset
Pandas Function

Statistics & Probability

Descriptive Statistics and Inferential Statistics
Sample and Population
Variables and Data Types
Percentiles
Measure of Central Tendency
Measures of Spread
Skewness, Kurtosis
Sampling Distribution
Introduction to Probability, Discrete and Continuous Distributions
Standard Probability Distribution Functions
Bernoulli, Binomial Distributions
Descriptive Statistics and Inferential Statistics in Python
Normal Distributions
Test of Hypothesis - Z Test, T-Test and Chi-square Test
Confidence Interval
Variance, Covariance, Correlation
Degrees of Freedom
ANOVA Test
Python Revision (NumPy, Pandas, Scikit Learn, Matplotlib)

Introduction to R Programming

Introduction to R
Data Types in R
How To Install R & R Studio
Data Structures in R
Programming Statistical
R-Packages
Predictive Analysis in R

Machine Learning

What is Machine Learning?
Machine Learning Use-Cases
Machine Learning Categories
Machine Learning Process Flow
Machine Learning Types

Supervised Learning

Implementing Different Types of Supervised Learning Algorithms
What are Classification and its Use Cases?
Confusion Matrix
Evaluating Model Output
Implementation of Logistic Regression
What is Decision Tree?
Algorithm for Decision Tree Induction
Creating a Perfect Decision Tree
What is a Random Forest?
Advanced Methods in Machine Learning
Dimensionality Reduction

Unsupervised Learning

What is Clustering & its Use Cases?
What is K-means Clustering?
How does the K-means algorithm work?
Implementing K-means Clustering
What is C-means Clustering?
Implementation of Clustering - Various Types
What is Hierarchical Clustering?
Implementing Hierarchical Clustering
How to do Optimal Clustering

Dimensionality Reduction

Introduction to Dimensionality
Why Dimensionality Reduction
Implementing Dimensionality Reduction Technique
PCA
Scaling Dimensional Model
Feature Engineering
Regularization
Underfitting vs Overfitting
Boosting, Bagging, and Random Forest
Cross Validation

Model Selection and Boosting

What is Model Selection?
The Need for Model Selection
Cross-Validation
What is Boosting?
How Boosting Algorithms Work?

Association Rules Mining and Recommendation Systems

What are Association Rules?
Calculating Association Rule Parameters
Association Rule Parameters
How does Recommendation Engines Work?
Content-Based Filtering
Collaborative Filtering
Market Basket Analysis
Apriori Algorithm

Time Series Analysis

What is Time Series Analysis?
Components of TSA
Importance of TSA
TSA in Python
TSA Forecasting
AR model
MA model
ARMA model
ARIMA model
Generating the ARIMA plot
Stationarity
Converting a non-stationary data to stationary
ACF & PACF
Plot ACF and PACF
Implementing the Dickey-Fuller Test

Natural Language Processing

Tokenization and Text Normalization
Exercise: Tokenization and Text Normalization
Exploring Text Data
Part of Speech Tagging and Grammar Parsing
Exercise: Part of Speech Tagging and Grammar Parsing
Implementing Text Pre-processing Using NLTK
Exercise: Implementing Text Pre-processing Using NLTK
Natural Language Processing Techniques Using spaCy
Introduction to Text Feature Engineering
Count Vector, TFIDF Representations of Text
Exercise: Introduction to Text Feature Engineering
Understanding Vector Representation of Text
Exercise: Understanding Vector Representation of Text
Understanding Word Embeddings
Word Embeddings in Action - Word2Vec
Word Embeddings in Action – Glove
Chat GPT Use case

Reinforcement Learning

What is Reinforcement Learning
Elements of Reinforcement Learning
Why Reinforcement Learning
Implement Reinforcement Learning using Python

Introduction to Deep Learning

What is Reinforcement Learning
Elements of Reinforcement Learning
Why Reinforcement Learning
Implement Reinforcement Learning using Python

Deep learning for computer vision

Image formation
Image representation
Linear filtering
Image sampling
Edge detection
Edges to Blobs and corner detection
Image segmentation
Human visual systems
Feature matching
Image description matching
From traditional vision to computer vision
Feedforward Neural network and backpropagation
Gradient Descent and variants
Regularization in Neural Network
Convolutional Neural Network
Backpropagation in CNN
Evolution of CNN architecture
Recent CNN architecture
CNN for object detection
CNN for segmentation
Recurrent Neural Network
Backpropagation in RNNs

Data Visualization using (Qlik sense) Optional Tools:

Snowflake (Basics)

Alteryx (Basics)

Data Iku (Basics)

Data Science Training Course Key Features

Will Power Technologies provides Data Science training courses designed for both beginners and experienced professionals. Our programs aim to equip you with in-demand skills and the expertise needed to excel in the ever-evolving field of Data Science.

Experienced Professionals: Our trainers are seasoned Data Science experts with extensive industry experience. Their hands-on approach and deep knowledge ensure that you gain practical skills and insights to solve real-world data challenges effectively.
State-of-the-Art Tools: We leverage the latest tools, frameworks, and technologies in Data Science to deliver cutting-edge training. This ensures you stay up-to-date with current industry standards and are well-prepared for modern data-driven roles.
Customized Learning Pathways: Our courses are designed to cater to individual learning needs, offering personalized training paths. Whether you're a novice or looking to upskill, we adapt the course content to suit your career goals.
Practical Integration: Our training emphasizes the seamless application of Data Science techniques across diverse industries. We focus on integrating data analytics, machine learning, and AI into your skillset to enhance business decision-making and productivity.

Skills Covered

Will Power Technologies provides training courses that cater to both beginners and experienced developers. Our programs are designed to equip you with the necessary skills and knowledge to excel in the software industry.

System Administration: Gain expertise in managing and maintaining mainframe hardware and software, including user management, system security, and backup and recovery procedures.
Application Development: Learn to develop and enhance applications specifically for mainframe environments. This includes understanding programming languages and tools used in mainframe development.
Data Migration: Master techniques for secure and efficient data transfer, ensuring data integrity and addressing any challenges that may arise during the migration process.
System Optimization: Acquire skills in performance monitoring and optimization, focusing on improving system efficiency and implementing enhancements to boost overall performance.
Integration: Develop the ability to connect mainframe systems with other business applications, facilitating smooth data exchange and synchronization to streamline processes.

Pre Requisites

No prior coding knowledge is required. While basic mathematics and programming knowledge are beneficial, our course is designed to accommodate learners from various backgrounds.

Enroll in Data Science Training Today!

Take the first step towards a rewarding career in data science with our Data Science Training Course at Will Power Technologies. Our comprehensive, hands-on approach ensures you gain the skills, certifications, and confidence to analyze data, build models, and unlock the power of data for any organization.

Join Will Power Technologies—where your journey to becoming a data science expert begins.

Course Information

Instructor: Shiva
Lessons: 20
Duration: 20 Weeks
Course level: Beginners
Language: English/Telugu
Students: 170+

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