Data Science Course in Pune

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Data Science Course in Pune

Master the Art of Data Science with Data Science Course in Pune at Cyber Success

In today’s era of a data-driven business world, businesses in every sector are using Data Science to drive their growth, make informed decisions and stay ahead of the competitive landscape. The importance of Data Science professional skills is growing rapidly. The professional data Scientist uses data science to drive innovation, improve decision-making, and gain competitive advantage. At Cyber Success IT Training Institute, we offer the Data Science Course in Pune. Our comprehensive Data Science Course in Pune is carefully designed to give you the skills, abilities and hands-on skills you need to excel in this ever-evolving industry.

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Significance of Data Science by Cyber Success's Data Science Course in Pune

Data Scientist analyzes raw data to identify valuable insights, patterns and trends that can guide strategic decision making. It is a multidisciplinary approach that combines principles and practices from the fields of mathematics, statistics, artificial intelligence, and computer engineering to analyze large amounts of data. At Cyber ​​Success IT Training Institute, Pune, we offer Data Science Course in Pune that covers all the concepts from basic to advanced technology to become a data professional. Experienced data science professionals can use advanced analytical tools and techniques to turn big data into actionable intelligence. This enables organizations to increase productivity, increase profitability, and achieve success. Data science covers various industries like finance, healthcare, commerce and e-commerce, emphasizing the importance of enrolling in our Data Science Course in Pune. Whether it’s optimizing marketing strategies, improving customer experience, streamlining operations, or identifying new revenue streams, our Data Science Classes in Pune highlight the importance of data science for businesses emphasizing all scales.

Key Advantages of Data Science Course at Cyber Success

  1. Advanced Learning:

At Cyber Success, our Best Data Science Course in Pune covers wide range of topics, like Python, SQL, AI, NPL, Machine Learning, and Data Visualization like Power BI, Tableau, MongoDB, and EDA, data cleaning, deep learning and etc. Our Data Science Course will initially provide a solid foundation necessary for success theories and strategies.

  1. Hands-On Practice:

We emphasize hands-on learning through practical activities and projects in our Data Science Course in Pune. This practical approach helps you to apply theoretical skills to real-world situations, increasing your practical knowledge and confidence in data science.

  1. Related Professional Knowledge:

We have designed our curriculum with industry professionals to ensure they are aligned with current industry trends and needs. You will learn the latest tools, technologies and techniques in the field, preparing you for real-world challenges with our Data Science Classes in Pune.

  1. Personal guidance:

Each student who enrolls in our Data Science Training in Pune receives personal guidance and advice from experienced instructors throughout the course journey. Whether you need help understanding complex concepts or professional development guidance, our trainers are committed to success.

  1. Placement Assistance:

Through our Data Science Course with Placement, we offer comprehensive recruitment assistance to help you land a successful career with Data Science skills. From resume building and interview guidance to placement assistance and networking opportunities, we provide the resources and support you need to achieve your career goals.

  1. Easy Learning Methods:

We offer flexible learning options, including classroom lectures and online batches. You can choose Online Data Science Course as well as Offline Data Science Course Batch at your convenience.

Eligibility Requirements for the Data Science Course

  • Educational Information:
    A bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, or a related field is preferred.

  • Basic accounting and statistical skills:
    Students should be proficient in statistics and probability theory and understand the advanced research methods covered in Data Science Classes in Pune.

  • Basic Skills:
    While learning Python, SQL, and other programming languages is beneficial, however beginners with a willingness to learn are also welcome to enroll in our Best Data Science Courses in Pune.

  • Research Skills:
    In data science, strong analytical and problem-solving skills are critical for data interpretation, pattern identification, and meaningful insights.

  • Communication Skills:
    Collaboration and effective oral and written communication are useful in research presentations.

Key Features of the Data Science Classes in Pune at Cyber Success

  • Hands-On Project Experience: With our Data Science Course in Pune, get involved in practical projects and real-world case studies to apply theoretical concepts and improve your practical data science skills has been great.
  • Expert Training: Learn from expert instructors who are industry professionals with extensive knowledge of data science, offering valuable insights and guidance.
  • Industry-Recognized Certification: Upon successful completion of the course, you will earn a data science certificate that is widely recognized in the industry and demonstrates your expertise in data science.
  • Ongoing Learning Support: Access to additional learning materials, online communities, and ongoing support after course completion, to ensure continued education and continued professional development in data science.

Why Cyber Success Stands Out as The Best Data Science Training Institute in Pune, India

In our Data Science Classes in Pune, we offer advanced training that is designed to equip individuals with the skills and knowledge needed to excel in the field of data science. Here’s why our Data Science Course is considered the best in Pune:

1. Python programming language (Pandas Library and NumPy):

Python for Data Science
Data Manipulation with Python levering Pandas and NumPy

Python is widely recognized as one of the most versatile and powerful programming languages in data science. Python’s simplicity, readability, and extensive libraries make it ideal for use, editing, and analysis. Learning Python is essential for automating tasks, performing complex calculations, and creating custom scripts and applications for data processing. The Pandas and NumPy libraries are especially useful for data analysts:

  • Pandas: This library provides efficient data structures and tools for working with structured (labeled) data, making it an essential tool for data analysts. It enables efficient data manipulation, cleaning, and transformation, making it a fundamental tool for data science.
  • NumPy: Important for scientific calculations and numerical applications NumPy provides support for large multidimensional arrays and matrices with large collections of efficient mathematical functions.

2. Advanced Excel and SQL (Structured Query Language):

Learn Excel and SQL in Data Science Classes in pune
Mastering SQL, Excel Database for Data Science

Advanced Excel: Excel is a widely used and industry standard tool for organizing, analyzing and visualizing data. It provides an easy-to-use interface and a wide range of functions and features that enable efficient data manipulation, auditing and organization. Advanced Excel skills, such as using pivot tables, VBA macros, and advanced formulas, are invaluable to data analysts as they simplify operations and increase productivity.

Advanced SQL: SQL is a language used to interact with relational databases, which is a staple in most organizations’ data warehouse infrastructure. SQL knowledge is important for data analysts because it allows them to extract, manipulate and analyze data stored in a database. SQL enables you to capture, filter, organize, and aggregate data efficiently, making it an essential skill for working with big data and complex queries.

3. Visualization Tools:

Data Science Training in Pune
mastering Data-driven visualization Power BI, Tableau, EDA the story behind the Number

Data visualization is essential to effectively communicate insights and findings. Presenting hard data is critical to creating engaging and informative charts, graphs, and dashboards. Our Data Science Classes includes visualization tools e.g.

  • Power BI: A powerful business intelligence and data visualization tool that enables analysts to create interactive and visually stunning reports and dashboards.
  • Tableau: Another popular data visualization tool that allows analysts to create interactive and highly visual dashboards, charts, and reports.
  • Exploratory Data Analysis (EDA): EDA is a method of analyzing and visualizing data to understand its fundamental characteristics. It summarizes the main features of the data set, often using mathematical modeling and other data visualization techniques.

4. MongoDB:

MongoDB for Data Science
MongoDB for seamless Data Management

MongoDB is a popular NoSQL database management system that stores data in flexible documents, such as JSON with dynamic schemas. It is particularly useful for processing large amounts of unstructured or semi-structured data, making it a valuable tool for data analysts working with data sources.

5. Mastering Learning Languages:

Data Science Course in Pune
With AI, ML,NPL shaping the future of Data Science

With a comprehensive understanding of how AI, ML, and NLP can be applied to solve real-world problems and extract valuable insights from data.

  • Artificial Intelligence (AI): In data science, AI is used to develop algorithms and models that can analyze data, make predictions and automate operations.
  • Machine Learning (ML): ML is a subset of AI that focuses on algorithms and mathematical models that enable computers to make predictions or decisions based on data ML is used in data science to develop predictive models and make sense of large data sets in.
  • Natural Language Processing (NLP): In data science, Natural language processing (NLP) is a machine learning technology that gives computers the ability to interpret, manipulate, and comprehend human language.

6. Statistics:

Statistics in Data Science Course
From Statistics to Insights Enhancing Data Science Proficiency
Statistics is the study of the collection, analysis, interpretation, presentation, and organization of data. Statistics plays a vital role in data science, enabling analysts to identify patterns, relationships, and trends in large and complex data sets. Using statistical methods, data scientists can extract insights and reliably interpret results.

7. Data cleaning:

Learn Deep Cleaning with Data Science Course in Pune
Data Cleaning For Data Science
Data cleaning is the process of identifying and correcting errors, inconsistencies and missing values in data processing. Data cleaning includes tasks such as eliminating duplicates, dealing with missing data, and standardizing data structures.

8. Deep learning:

Deep Learning with Data Science Classes in Pune
Deep Learning For Data Science

Deep learning is a subset of machine learning that focuses on building and training muscles. Deep learning has been used in a variety of applications, including image recognition, speech recognition, and natural language processing.

By acquiring these essential elements in Data Science Course in Pune, individuals will develop the skills necessary to effectively gather, process, analyze, and communicate data-driven insights. These skills are increasingly important in today’s data-driven world, where organizations rely on data-driven decision-making to gain competitive advantage. To know more Contact Us.

The Transformative Power of Data Science Across Industries

Changing business dynamics: The critical role of data science in delivering innovation, streamlining operations and sustainable growth in industries is led by the Cyber ​​Success’s Data Science Course in Pune. Data science is not static; It is a transformative force that is reshaping the world’s industries. Data science plays a critical role in driving innovation, increasing business efficiency, and driving success for industries from finance to healthcare and beyond Here’s a detailed look at how different industries is harnessing the potential of data:

Job Opportunities with Data Science Course with Certificate

Chart Your Course to Data Science Success: Choose Cyber Success in Pune

Interactive classroom:

Enjoy learning sessions at our Data Science Classes, where our experienced trainers enlighten your mind, facilitate group discussions and conduct practical demonstrations. This interactive learning environment ensures a deep understanding of concepts and effective use of data analysis

Fundamental Learning:

Our accredited data science course with certification starts with the basics, offering a step-by-step learning approach that gives you the skills you need. You will learn from basics to advanced topics, ensuring you have a solid foundation for your data science journey.

Advanced Learning:

Curriculum of our Best Data Science Classes in Pune are carefully designed by industry experts, so that you get detailed and clear explanations for all your questions. We cover the latest methods, techniques and best practices, equipping you with the knowledge and skills needed to get the job done.

Professional Development:

Our accredited data science course with certification starts with the basics, offering a step-by-step learning approach that gives you the skills you need. You will learn from basics to advanced topics, ensuring you have a solid foundation for your data science journey.

Hands-On Learning:

We emphasize practical learning, bridging the gap between theory and real-world application with hands-on activities. This approach ensures that you develop the skills you need to confidently analyze complex issues and solve real-world problems.

Why Choose the Data Science Certification Course at Cyber Success Pune?

cyber success certificate

Enrolling in our Data Science Course with Certification in Pune at Cyber Success in Pune, whether through an online class or office batches, opens doors to a promising career path, exposes your skills in data science and enhances your prospects in the IT sector. Our Data Science Certificate demonstrates your commitment to professional development, which sets you apart as an experienced Data Scientist. In today’s rapidly evolving technological environment, such a recognized credential is a valuable asset, giving you a competitive edge in job interviews and boosting your career. Whether you are starting your journey in data or looking to enhance your current skills, our Data Science Course with Certification in Pune at Cyber Success offers a pathway to a rewarding and successful career in IT.

The benefits of getting a Data Science Certificate through our Data Science Classes in Pune are extensive and tailored to your career goals and aspirations. Through our Data Science Certificate, you will validate your skills and get strategic advantages while entering the job.

Known for its versatility and importance across industries, as evidenced by its use in companies such as Google, Netflix and Uber, it is in high demand among professionals Training certifications not only build credibility but also open doors for many career opportunities. With data science certifications becoming increasingly recognized worldwide, employers often prioritize candidates with these credentials when making hiring decisions or considering promotions, and they make smart money to grow your careers.

After completing the Data Science Classes at Cyber Success Pune, you'll showcase a range of valuable skills:

  • Data Analysis Skills:
    • Proficiency in statistical analysis techniques such as hypothesis testing, regression analysis, and descriptive statistics taught in Data Science Course in Pune.
    • An important part of learning is being able to analyze data and gain insights.
  • Data Visualization Skills:
    • Proficiency in data visualization tools such as Tableau and Power BI.
    • Application of visualization techniques emphasized throughout the Data Science Classes in Pune to present findings effectively.
  • Functional Skills:
    • Strong programming skills in Python, including use of libraries such as Pandas for data manipulation and Seaborn for data visualization integral parts of the Data Science Course curriculum.
  • Database management capabilities:
    • Develops SQL skills to query and maintain relational databases covered extensively in the Data Science Classes.
    • MongoDB and other known NoSQL databases for unstructured data processing.
  • Work Experience:
    • Develops SQL skills to query and maintain relational databases covered extensively in the Data Science Classes.
    • Understanding how data analysis contributes to organizational goals, a key takeaway from the Data Science Course.

Completing a Data Science course at Cyber ​​Success will provide you with strong skills that prepare you for a career in Data Science and enable you to excel in industries where data-driven decision-making is critical.

Data Science Classes Key Features at Cyber Success Pune

Course Duration

50 Hours

Enhance your learning experience with up to 50 hours of hands-on learning. Our specialist tutors will provide individualized work tailored to your skills and learning objectives, ensuring maximum engagement and skills development.

Skill Level

Beginner to Advance

From beginners to advanced, our Data Science Course caters to students of all levels. Whether you are starting from scratch or looking to advance your skills, our training program is designed to meet your individual needs and goals.

Total Learners

2000+ Learners

Join over 2000 students who have already benefited from our Data Science Course. With over 100 batches completed and 100% completion, Cyber Success is your trusted partner in data science education.

Assignments Duration

50 Hours

50 Hours Enhance your learning experience with hands-on assignments spanning 50 hours. Our expert trainers will provide personalized assignments tailored to your skill sets and learning objectives, ensuring maximum engagement and skill development.

Classroom Options

Online-Offline

Enjoy the flexibility of choosing between online and offline classroom courses. Whether you prefer convenient distance learning or face-to-face meetings, Cyber Success meets your learning needs.

Class Schedules

Weekday and weekend

With a flexible curriculum offering weekday and weekend sessions, our Data Science Course meet the needs of professionals and students. Choose between morning or evening sessions to accommodate your busy schedule and balance studying with other commitments.

Fees

Competitive pricing

Take advantage of competitive pricing for our data science course fees, as well as on-site support to launch your career in data science. We offer flexible payment options, including payment plans, to ensure access for all students.

Scholarship Program

Campus Connect

Campus Connect Explore scholarship opportunities through our Campus Connect program, designed to support deserving candidates and alleviate the financial burden of the course. At Cyber Success, we’re committed to making quality education accessible to everyone.

Trainer’s Profile For Data Science Course in Pune in Cyber Success

  • Industry experts: Our trainers are experienced professionals with extensive experience in data science.
  • Advanced degree: Each teacher has an advanced degree in a related field such as mathematics, computer science, or data science.
  • Hands-on experience: With years of experience in data science industries, our instructors bring real-world insights to the classroom.
  • Certifications: Many of our instructors have industry certifications in data science, demonstrating their skills and commitment to excellence.
  • Teaching Experience: With exceptional teaching skills, our teachers are adept at simplifying complex concepts and ensuring that students understand them.
  • Individual Attention: Our teachers provide individualized attention to each student, addressing individual learning needs and providing a supportive learning environment.
  • Current curriculum: Keeping abreast of the latest trends and advancements in data science, our instructors ensure that the curriculum is relevant and up-to-date.
  • Career guidance: In addition to technical education, our professors provide valuable career guidance, helping to guide students on the path to a successful career in data science.
  • Passion for Education: Above all, our professors are passionate about education and dedicated to equipping students with the knowledge and skills they need to succeed in data science.

After completing our Data Science Course in Pune, you will have the skills to navigate the complexities of data. Through in-depth training and practical experience, the data science course empowers individuals to enter the advanced world of data-driven decision-making. With appropriate instruction and hands-on activities, data science courses enable individuals to fully participate in data-driven decision-making Let’s explore how such courses can improve your knowledge and confidence in using data in reliability has improved.

Cyber Success Data Analytics Course in Pune: Syllabus

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Cyber Success Data Science Course in Pune: Syllabus

  1. Introduction To Python
  • What is Python?
  • Where and how it is used?
  • Why Python Over Others?
  • Alternative Python Implementations
  • Versions 3.X
  • Introduction of PYPI
  • Introduction of Pep8
  • Zen of Python
  1. Installation & Environment Setup
  • Installation of Python
  • Introduction to IDE (Vscode, Py-charm Jupiter-notebook)
  • Different ways to run Python Code.
  • Write First Program
  • Multiline Print Statement
  • Comments in python
  1. Variables and Data Types
  • Variables
  • int, float, complex number
  • String
    • Introduction, Indexing, Slicing and Iteration,
    • String Functions.
  • List
    • List Introduction, Iteration, slicing,
    • List Functions, List Comprehension
    • List Comprehension
  • Tuple
    • Introduction, Iterations, Function, making tuples Multables
  • Dictionary
    • Creation of Dictionaries, Iterations
    • Dictionary Functions and Nested
    • Dictionaries, Dictionary Comprehension
    • Dictionary Comprehension
  • Sets
    • Introduction, Iterations, Set Methods
  1. Keywords and Operators
  • Keywords in Python
  • Operators in Python
  1. Operations with Data Types
  • String functions
  • List Comprehension
  • Dictionary Comprehension
  1. Program Flow Control
  • Conditional Statements
  • Loops
  • Types of Loops
    • For Loops
    • While Loops
  • Loops with conditional statement
  • Infinite Loop
  • Nested Loops
  • Break and Continue Statement
  • Block Structure
  1. Functions
  • Introduction, Types, Parameters, arguments
  • Argument Types
  • Positional Argument
  • Default Argument
  • Keyword Argument
  • Lambda Functions
  • Inner Functions
  • Closures
  1. OOPs – Object Oriented Programming
  • What Is OOP?
  • Creating Our own Objects
  • Attributes and Methods
  • _ _init. _ _
  • Encapsulation
  • Abstraction
  • Private vs Public Variables
  • Inheritance
  • Polymorphism
  • super()
  1. Special Concepts
  • Iterator
  • Generator
  • Decorator
  1. Module & Packages
  • In Built
  • User Defined
  • Third Party
  1. Exception Handling
  • What is the Exception
  • What is Exception Handling?
  • try-except-finally blocks
  1. File Handling
  • What is File
  • Various File Handling Operations
  • File operation using.csv & txt
  1. Regular Expressions
  • Introduction to Regular Expression
  • Operation using the RegEx module

1. Data Science with Pandas

  • Installing Jupyter Notebook
  • How to use Jupyter Notebook?
  • Introduction to Pandas
  • Installing Pandas
  • DataFrames- Working with Columns
  • DataFrames-Working with Rows and Columns
  • Filtering Data
  • Reading and Analysing CSV Files with Pandas
  • Reading Excel Files: GroupBy and Other
  • Useful Operations
  • Working with Missing Data
  • Merging and Concatenating Files in Pandas
  • Dealing with duplicates in Pandas
  1. NumPy
  • Introduction to NumPy
  • 1-D Array
  • 2-D Array
  • Indexing
  • Slicing
  • Concatenating
  • Broadcasting
  • Statistical functions
  • Arithmetic functions
  1. Data Visualization Using Matplotlib
  • Introduction to Python Visualization Libraries
  • Installing Matplotlib
  • Creating Scatter Plots
  • Creating Line Charts
  • Creating Basic Bar Charts
  • Creating Grouped and Stacked
  • Bar Charts
  • Creating Pie Charts
  1. Data Visualization Using Seaborn
  • Introduction to Python Visualization Libraries
  • Installing Seaborn
  • Creating Scatter Plots
  • Creating Line Charts
  • Creating different types of Charts in Seaborn

Basic SQL

  • Introduction to SQL
  • Installation
  • Data Types in MySQL
  • Clauses in MySQL
  • Operators in MySQL
  • Set Operations
  • Group By
  • Having Clause
  • Case Operators

Advanced SQL

  • Joins in Database
  • Stored Procedures
  • Window functions
  • Subqueries
  • Common Table Expressions
  • Views in MySQL

  1. Introduction to Excel for Data Analysis
  • Overview of Excel’s Data Analysis Capabilities
  • Understanding Excel’s Interface for Data Analysis
  • Basic Excel Functions and Formulas for Data Manipulation
  1. Data Import and Data Cleaning in Excel
  • Importing Data from External Sources: CSV, Text Files, Databases, etc.
  • Understanding Data Types and Formatting
  • Data Cleaning Techniques: Removing Duplicates, Handling Missing Values, etc.
  • Using Text Functions for Data
  • Cleaning and Transformation
  1. Data Analysis Tools in Excel
  • Introduction to Excel’s Data Analysis Tools (e.g., PivotTables, Power Query)
  • Creating PivotTables for Data Summarization and Analysis
  • Performing Data Analysis with PivotTables: Filtering, Sorting, Grouping, etc.
  • Using Conditional Formatting for Data Visualization
  1. Advanced Data Analysis Techniques
  • Advanced PivotTable Features: Slicers, Timelines, Calculated Fields etc.
  • Introduction to Excel’s Statistical Functions
  • Performing Descriptive Statistics: Mean, Median, Standard Deviation, etc.
  1. Visualizing Data in Excel
  • Creating Basic Charts: Bar charts, Line charts, Pie charts, etc.
  • Customizing Charts for Clarity and Effectiveness
  • Creating Interactive Dashboards with Excel Charts and Slicers
  1. Data Analysis with Excel Functions
  • Introduction to Excel Functions for Data Analysis (e.g., VLOOKUP, INDEX-MATCH)
  • Using Logical Functions for Data Analysis: IF, AND, OR, etc.
  • Performing Date and Time Analysis with Excel Functions
  • Using Lookup and Reference
  • Functions for Data Analysis Tasks
  1. Real-World Data Analysis Projects
  • Analyzing Sales Data and Trends
  • Financial Data Analysis and Reporting
  • Marketing Campaign Analysis
  • HR Data Analysis: Employee Performance, Turnover, etc.
  • Supply Chain Analysis and Optimization

  1. Introduction to Power BI
  • Overview of Power BI
  • Understanding the Power BI ecosystem
  • Installation and setup
  • Power BI Desktop vs. Power BI Service
  1. Getting Started with Power BI Desktop
  • Introduction to Power BI Desktop Interface
  • Importing Data into Power BI Desktop
  • Transforming Data using Power Query Editor
  • Data Modeling in Power BI Desktop
  • Creating Relationships between Tables
  1. Data Visualization Basics
  • Introduction to Data Visualization Principles
  • Building Basic Visualizations: Bar charts, Line charts, Pie charts, etc.
  • Formatting Visualizations for Clarity
  • Using Filters and Slicers
  • Adding Interactivity with Drill-Downs and Drill-Throughs
  1. Advanced Data Visualization Techniques
  • Utilizing Custom Visuals
  • Creating Hierarchies and Groups
  • Implementing Conditional Formatting
  • Incorporating KPIs and Gauges
  • Working with Maps and Geographic Data
  1. Advanced Data Modeling
  • Understanding DAX (Data Analysis Expressions)
  • DAX Functions: CALCULATE, FILTER, SUMX, etc.
  • Creating Calculated Columns and Measures
  • Time Intelligence Functions
  • Handling Hierarchies and Parent-Child Relationships
  1. Power BI Service and Collaboration
  • Introduction to Power BI Service
  • Publishing Reports and Dashboards
  • Sharing and Collaborating on Power BI Content
  • Managing Security and Permissions
  • Setting up Data Gateways for On-Premises Data
  1. Data Connectivity and Integration
  • Connecting to Various Data Sources: Excel, SQL Server, Share-Point, etc.
  • Importing vs. Direct Query vs. Live Connection
  • Refreshing Data Automatically
  • Integrating Power BI with Other
  • Microsoft Tools (Excel, Teams, SharePoint)8. Real-World Projects and Case Studies
  • Building End-to-End Dashboards from Scratch
  • Analyzing Sales Data
  • Financial Reporting and Analysis
  • Marketing Analytics
  • Interactive Executive Dashboards

  1. Introduction to Tableau
  • Overview of Tableau and its Capabilities
  • Understanding the Tableau Product Suite
  • Installation and Setup
  • Tableau Desktop vs. Tableau Server vs. Tableau Online
  1. Getting Started with Tableau Desktop
  • Introduction to Tableau Desktop Interface
  • Connecting to Data Sources
  • Basic Visualization Building
  • Blocks: Marks, Dimensions, and Measures
  • Creating Basic Visualizations: Bar charts, Line charts, Scatter plots, etc.
  • Data Sorting and Filtering
  1. Advanced Data Visualization Techniques
  • Customizing Visualizations with Formatting and Labels
  • Using Sets, Groups, and Hierarchies
  • Implementing Calculated Fields and Parameters
  • Creating Interactive Dashboards
  • Incorporating Trend Lines, Reference Lines, and Forecasting
  1. Advanced Data Analysis with Tableau
  • Understanding Tableau’s Data Blending and Joins
  • Introduction to Table Calculations
  • Advanced Calculations using LOD (Level of Detail) Expressions
  • Performing Statistical Analysis within Tableau
  • Advanced Mapping Techniques
  1. Dashboard Design and Best Practices
  • Principles of Effective Dashboard Design
  • Designing Interactive Dashboards for User Engagement
  • Incorporating Action Filters and Highlighting
  • Dashboard Layouts and Formatting
  • Mobile Optimization for Tableau Dashboards
  • Tableau Server and collaboration
  • Introduction to Tableau Server
  • Publishing Workbooks to Tableau Server
  • Sharing and Collaborating on Tableau Content
  • Managing User Permissions and Access
  • Setting up Data Extracts and Schedules
  1. Data Connectivity and Integration
  • Connecting to Various Data Sources: Excel, SQL Server, Sales-force, etc.
  • Using Data Blending for Data Integration
  • Refreshing Data Automatically
  1. Advanced Topics
  • Tableau Prep: Data Preparation and Cleaning
  • Tableau Extensions for Advanced Functionality
  1. Real-World Projects and Case Studies
  • Building Interactive Dashboards for Sales Analysis
  • Visualizing Customer Segmentation and Market Trends
  • Analyzing Financial Performance
  • Exploring Social Media Analytics
  • Creating Executive Dashboards for Decision Making

  1. Introduction to NoSQL databases
  • Overview of SQL vs NoSQL
  • Types of NoSQL databases
  • Advantages and disadvantages of NoSQL databases
  1. Understanding MongoDB architecture
  • Document-oriented data model
  • Collections and Documents
  • BSON (Binary JSON)
  1. Installing MongoDB
  • Installation on different platforms (Windows, macOS, Linux)
  • Configuration and setup
  1. CRUD operations in MongoDB
  • Inserting documents
  • Querying documents
  • Updating documents
  • Deleting documents
  1. Querying MongoDB
  • Basic queries
  • Query operators (comparison, logical, element, etc.)
  • Aggregation Framework
  1. Indexing and Aggregation
  • Index types (single field, compound, multikey)
  • Performance optimization with indexing
  • Aggregation pipeline stages
  1. Data modeling in MongoDB
  • Schema design principles
  • Embedding vs Referencing
  • Modeling relationships (one-to-one, one-to-many, many-to-many)
  1. MongoDB Atlas – Cloud database hosting
  • Introduction to MongoDB Atlas
  • Creating and configuring clusters
  • Data backup and restore
  1. Security in MongoDB (Optional)
  • Authentication mechanisms (SCRAM, X.509 certificates)
  • Role-based access control (RBAC)
  • Encryption in transit and at rest

10. Web Scraping in Python

  • Working with Beautiful Soap
  • Parsing HTML and XML
  • Navigating the document

  1. Introduction to Data Science
  • What is Data Science?
  • What does data science involves?
  • Application and Scope of Data Science?
  • Life cycle of Data Science
  • Tools of Data Science
  • Training Data, Test Data & Validation Data
  • Supervised and Unsupervised ML, Artificial Intelligence Vs Machine
  • Learning Vs Data Science
  • Types of attributes in Machine Learning problem

  • Understanding the definition of Statistics?
  • Understanding data, sample and population
  • Types of data Qualitative and Quantitative
  • Descriptive Statistics
  • Uni-variate Data Analysis – Measure of Central Tendency
  • Mean, Median and Mode
  • Uni-variate Data Analysis Measure of Dispersion
  • Range, Variance, Standard Deviation,
  • Bi-variate Data Analysis Covariance and Correlation
  • Inferential Statistics
  • Central Limit Theorem
  • Normal Distribution
  • Binomial and Poisson Distributions
  • Skewness
  • What is Hypothesis Testing?
  • Null and Alternate Hypothesis
  • P-value, Level of significance
  • Confidence Level and Confidence Interval
  • One Sample 2-test
  • T-test, Z test
  • Chi Square Test

Introduction to Feature Engineering and Data Cleaning

  • Overview of Feature Engineering, EDA, and Data Cleaning
  • Data Cleaning Techniques: Handling Missing Values (Imputation, Removal)
  • Data Cleaning Techniques: Handling Outliers and Anomalies
  • Data Transformation Techniques: Scaling and Normalization
  • Feature Engineering: Introduction and Importance
  • Feature Engineering Techniques: Encoding Categorical Variables (One-Hot Encoding, Label Encoding)
  • Exploratory Data Analysis (EDA)
  • Exploratory Data Analysis (EDA): Overview and Importance
  • Univariate Analysis: Histograms, Boxplots, and Frequency Tables
  • Bivariate Analysis: Scatter Plots, Correlation Analysis
  • Multivariate Analysis: heatmaps, Pair Plots, and Dimensionality Reduction Techniques
  • Advanced EDA Techniques: Feature Importance, Influence Plots
  • Hands-on Practice: Performing
  • EDA on Real-world Datasets
  • Advanced Feature Engineering and EDA Techniques
  • Feature Engineering: Feature Scaling Techniques (Min-Max Scaling, Robust Scaling)
  • Feature Engineering: Binning, Polynomial Features, and Interaction Terms
  • Feature Engineering: Handling Date and Time Variables
  • EDA for Time Series Data: Seasonality, Trend Analysis
  • EDA for Text Data: Word Frequency Analysis, Sentiment Analysis

  1. Regression Analysis
  • Understanding the working and equation of Regression Analysis
  • Regression metrics – R2-score, MAE, MSE, RMSE, Adjusted R Squared
  • Implementation of Simple & Multiple Linear Regression
  • Implementation of Ordinary Least Square(OLS) & Regularization
  • Project – Heating and Cooling Load Prediction
  1. Classification Analysis
  • Understanding the working of Classification Analysis
  • Implementation of Logistic Regression Understanding Confusion Matrix
  • Classification Metrics – Accuracy,
  • Precision, Recall, Fl-Score, auc and roc curve
  • Handling imbalanced datasets
  • Bias Variance, Underfitting and Overfitting
  • Project – Diabetic patient Classification
  1. Naive Bayes Algorithm
  • Understanding the working of Naive Bayes
  • Implementation of Naive Bayes Classification
  • Project – News Classification
  1. K-Nearest Neighbor (KNN) Algorithm
  • Understanding the working of KNN Classification & Regression
  • Algorithm of KNN & Implementation of KNN
  • Project – Social Network Ads Classification
  1. Tree based Models
  • Understanding the working of Decision Tree
  • Understanding Gini and Entropy criterion
  • Implementation of Decision Tree Classification & Regression
  • Project – Iris Flower Classification
  1. Support Vector Machine (SVM) Algorithm
  • Understanding the working of SVM Classification & Regression
  • Implementation of SVM Classification & Regression

  • Understanding the working of Random Forest Classification & Regression
  • Implementation of Random Forest Classification & Regression
  • Difference between Bagging and Boosting
  • Understanding the working of Ada-Boost
  • Implementation of AdaBoost

  • Understanding the working of Gradient descent
  • Type of Gradient descent
  • Understanding of Batch, Stochastic& mini batch Gradient Descent
  • Understanding the working of Cross-Validation
  • Types of Cross Validation (Train & Test , K- Fold, Stratified k-fold etc.)
  • Understanding the working of Model Parameter, Hyperparameter

  1. K-Means Clustering
  • Understanding the working of K-Means Clustering
  • Understanding of Elbow method to find optimal number of clusters
  • Project – Shopping dataset clustering
  1. Hierarchical & DESCAN and Clustering
  • Understanding and Implementation the working Hierarchical Clustering
  • Understanding of Agglomerative
  • Hierarchical (Single Linkage, Complete Linkage)
  • Understanding and Implementation the working DBSCAN Clustering
  • Project- Shopping dataset clustering2. Association Rule Learning
  • Understanding the working of Association Rule Learning
  • Understanding and Implementation of Apriori , Frequent Pattern, Growth Algorithm
  • Project – Market Basket Analysis3. PCA (Principal Component Analysis)
  • Understanding the working of PCA
  • Understanding Eigen values and Eigen vectors.
  • Implementation of PCA

  1. Neural Network & Tensor-Flow
  • Introduction to Neural Network
  • What is a Neuron?
  • Working of a Neuron
  • Perceptron Model
  • Concept of Hidden layers and Weights
  • Concepts of Activation Functions, Optimizers and Loss Functions
  • Equation of General Neural Network
  1. ANN (Artificial Neural Network)
  • Implementation of a Neural Network
  • Implementation of ANN for Regression
  • Implementation of ANN for Classification
  • Project – Customer Churn Modelling
  1. CNN (Convolutional Neural Network)
  • Understanding CNN (Convolutional Neural Network)
  • Understanding the Convolution process
  • Concept of Filter, strides
  • Pooling Layer
  • Fully Connected Layer
  • Project – MNIST Image Classification

  1. Natural Language Processing (NLP) Fundamentals
  • Introduction to NLP and its challenges
  • Text preprocessing: tokenization, stemming, lemmatization
  • Sentiment Analysis
  1. Advanced NLP techniques
  • Sequence-to-sequence models and their applications
  • Attention mechanisms: Transformer architecture
  • learning in NLP
  • Introduction to LLMs, Transformer, GANs & Cutting Edge Advancements in ChatGPT
  • Introduction to GANs, reinforcement learning, etc.
  • Ethical Al research and guidelines
  1. Image Processing using OpenCV
  • Reading and displaying an image using OpenCV
  • Image Transformation operations
  • Arithmetic Operations on Images
  • Draw Line, Rectangle, Circle, Ellipse and Polygons on Image
  • Object Detection using Haarcascade Files – Face and car Detection

OFFLINE DATA SCIENCE CLASSES IN PUNE

Batch Schedule for Data Science Course in Pune

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15 Oct

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Success Stories - Placed Students after Completing the Java Training classes at Cyber Success Pune
Witness the success stories of our students who’ve just completed the Java Certification Course at Cyber Success. They’ve already secured their futures with leading companies, all starting with a minimum package of 3+ LPA!

Frequently Asked Questions

Typically, there are no strict prerequisites for beginners’ Java training. Basic knowledge of programming concepts can be helpful, but many courses are designed for those new to programming.

It depends on your capability. Some find it easy, whereas some pick it up effortlessly. But we apply a student-centric approach with which we impart complete support till you master the language.

You can start working as a Java Developer, Web Developer, Application Developer, Software Developer, or Web Programmer.

All the sessions are live in which we give importance to interactive sessions. We insist on students for group discussion.

Sure, it will give insights into how we conduct our classes. It will help you decide whether you have an interest in the subject matter.

The course fees and duration depend on the module you choose. For more details, you may contact us.

We conduct mock interviews as well as you will receive interview calls for a fresher and professional profiles. We will help you to design your resume.

Yes, you will get a certificate of course completion.

We know the challenges faced by working professionals, so we have special batches designed for them.

Cyber Success is equipped with the best mentors from the IT industry. They impart knowledge that complements the latest trends of the market.

In Their Own Words: Student Feedback and Experiences

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