Description
Curriculum
Instructor
Duration :- 12 Months
Data Science Course – Code Codence Unlock the world of data-driven decision-making with Code Codence’s comprehensive Data Science course. Designed for beginners and professionals alike, this course offers a complete guide to mastering data science concepts, tools, and techniques.
What You’ll Learn:
- Data Analysis & Visualization: Learn how to gather, clean, and interpret data using powerful tools like Python, Pandas, and Matplotlib.
- Statistics & Machine Learning: Gain in-depth knowledge of statistical methods and machine learning algorithms to build predictive models.
- Data Wrangling: Handle messy data, perform exploratory data analysis, and discover insights from large datasets.
- Tools & Technologies: Get hands-on experience with Python, SQL, NumPy, SciPy, and more.
- Real-world Projects: Work on industry-relevant projects to enhance your portfolio and solve real data challenges.
Why Choose This Course?
- Affordable Learning: We believe in offering top-tier education at a fraction of the cost.
- Expert Mentors: Learn from industry experts who bring real-world experience into the classroom.
- Flexible Schedules: Attend live sessions or access recordings to learn at your own pace.
- Certification: Earn a certificate upon completion to boost your career prospects in data science.
Who Should Enroll?
- Aspiring data scientists
- Data enthusiasts
- IT professionals looking to upskill
- Anyone interested in making data-driven decisions
Enroll now at Code Codence and start your journey to becoming a data scientist!
For more details about the Data Science Using Python course, contact us here or chat with us directly on WhatsApp — we’re here to help you get started!
Curriculum
- 12 Sections
- 92 Lessons
- 52 Weeks
Expand all sectionsCollapse all sections
- PYTHON (3 Months)35
- 1.1Module 1: Introduction to Python
- 1.2Module 2: Writing and Executing Your First Python Program
- 1.3Module 3: Python Language Fundamentals
- 1.4Module 5: Python Conditional Statements
- 1.5Module 6: Looping Statements
- 1.6Module 4: Standard Data Types
- 1.7Module 7: String Handling
- 1.8Module 8: Python List
- 1.9Module 10: Python Set
- 1.10Module 9: Python Tuple
- 1.11Module 11: Python Dictionary
- 1.12Module 12: Python Functions
- 1.13Module 13: Modules & Packages
- 1.14Module 14: File I/O
- 1.15Module 15: Object Oriented Programming
- 1.16Module 16: Exception Handling
- 1.17Module 17: Regular Expressions (Regex)
- 1.18PYTHON1 Hour50 Questions
- 1.19Module 1 Introduction to Python (Assignment Questions)1 Week
- 1.20Module 2 Writing and Executing Your First Python Program (Assignment Questions)1 Week
- 1.21Module 3 Python Language Fundamentals(Assignment Questions)1 Week
- 1.22Module 4 Standard Data Types (Assignment Questions)1 Week
- 1.23Module 5 Python Conditional Statements (Assignment Questions)1 Week
- 1.24Module 6 Looping Statements (Assignment Questions)1 Week
- 1.25Module 7 String Handling (Assignment Questions)1 Week
- 1.26Module 8 Python List (Assignment Questions)1 Week
- 1.27Module 9 Python Tuple (Assignment Questions)1 Week
- 1.28Module 10 Python Set & Frozenset (Assignment Questions)1 Week
- 1.29Module 11 Python Dictionary (Assignment Questions)1 Day
- 1.30Module 12 Python Functions (Assignment Questions)1 Week
- 1.31Module 13 Modules & Packages (Assignment Questions)1 Week
- 1.32Module 14 File IO (Assignment Questions)1 Week
- 1.33Module 15 Object Oriented Programming (Assignment Questions)1 Week
- 1.34Module 16 Exception Handling (Assignment Questions)1 Week
- 1.35Module 17 Regular Expressions (Regex) (Assignment Questions)1 Week
- SQL (Structured Query Language)23
- 2.1Module 1: SQL Basics
- 2.2Module 2: DML, DDL & DQL
- 2.3Module 3: SQL Constraints
- 2.4Module 4: Querying Data
- 2.5Module 5: SQL Joins
- 2.6Module 6: SQL Functions
- 2.7Module 7: Aggregate Functions and Grouping
- 2.8Module 8: Subqueries and Nested Queries
- 2.9Module 9: Window Functions
- 2.10Module 10: Indexing and Performance Optimization
- 2.11Module 11: Data Warehousing Concepts
- 2.12Module 1 SQL Basics (Assignment Questions)1 Week
- 2.13Module 2 DML, DDL & DQL (Assignment Questions)1 Week
- 2.14Module 3 SQL Constraints (Assignment Questions)1 Week
- 2.15Module 4 Querying Data Assignment Questions1 Week
- 2.16Module 5 SQL Joins (Assignment Questions)1 Week
- 2.17Module 6 SQL Functions (Assignment Questions)1 Week
- 2.18Module 7 Aggregate Functions and Grouping (Assignment Questions)1 Day
- 2.19Module 8 Subqueries and Nested Queries (Assignment Questions)1 Week
- 2.20Module 9 Window Functions (Assignment Questions)1 Week
- 2.21Module 10 Indexing and Performance Optimization (Assignment Questions)1 Week
- 2.22Module 11 Data Warehousing Concepts (Assignment Questions)1 Week
- 2.23SQL (Structured Query Language)1 Hour50 Questions
- PYTHON LIBRARIES11
- 3.1Module 1: NumPy for Numerical Computing
- 3.2Module 2: Pandas for Data Manipulation
- 3.3Module 3: Data Visualization with Matplotlib
- 3.4Module 4:Data Visualization with Seaborn
- 3.5Module 5: Practical Applications and Case Studies
- 3.6Module 1 NumPy for Numerical Computing(Assignment Questions)1 Week
- 3.7Module 2 Pandas for Data Manipulation (Assignment Questions)1 Week
- 3.8Module 3 Data Visualization with Matplotlib (Assignment Questions)1 Week
- 3.9Module 4 Data Visualization with Seaborn (Assignment Questions)1 Week
- 3.10Module 5 Practical Applications and Case Studies (Assignment Questions)1 Week
- 3.11PYTHON LIBRARIES1 Hour50 Questions
- STATISTICS11
- 4.1Module 1: Introduction to Statistics
- 4.2Module 2: Understanding Population and Samples
- 4.3Module 3: Measures of Central Tendency and Dispersion
- 4.4Module 4: Probability and Probability Distributions
- 4.5Module 5: Hypothesis Testing
- 4.6Module 1 Introduction to Statistics (Assignment Questions)1 Week
- 4.7Module 2 Understanding Population and Samples (Assignment Questions)1 Week
- 4.8Module 3 Measures of Central Tendency and Dispersion (Assignment Questions)1 Week
- 4.9Module 4 Probability and Probability Distributions (Assignment Questions)1 Week
- 4.10Module 5 Hypothesis Testing (Assignment Questions)3 Days
- 4.11STATISTICS1 Hour50 Questions
- MACHINE LEARNING23
- 5.1Module 1: Introduction to Machine Learning
- 5.2Module 2: Supervised Learning
- 5.3Module 3: Unsupervised Learning
- 5.4Module 4: Support Vector Machines (SVM)
- 5.5Module 5: Decision Tree Classification
- 5.6Module 6: Ensemble Learning
- 5.7Module 7: Model Selection Techniques
- 5.8Module 8: Recommendation Systems
- 5.9Module 9: Text Analysis
- 5.10Module 10: Dimensionality Reduction
- 5.11Module 11: OpenCV
- 5.12Module 1 Introduction to Machine Learning (Assignment Questions)1 Week
- 5.13Module 2 Supervised Learning (Assignment Questions)1 Week
- 5.14Module 3 Unsupervised Learning (Assignment Questions)1 Week
- 5.15Module 4 Support Vector Machines (SVM) (Assignment Questions)1 Week
- 5.16Module 5 Decision Tree Classification (Assignment Questions)1 Week
- 5.17Module 6 Ensemble Learning (Assignment Questions)1 Week
- 5.18Module 7 Model Selection Techniques (Assignment Questions)1 Week
- 5.19Module 8 Recommendation Systems (Assignment Questions)1 Week
- 5.20Module 9 Text Analysis (Assignment Questions)1 Week
- 5.21Module 10 Dimensionality Reduction (Assignment Questions)1 Week
- 5.22Module 11 OpenCV (Assignment Questions)1 Week
- 5.23MACHINE LEARNING1 Hour50 Questions
- Deep Learning & Neural Networks27
- 6.1Module 1: Introduction to Artificial Neural Networks
- 6.2Module 2: Introduction to Deep Learning
- 6.3Module 3: TensorFlow Basics
- 6.4Module 4: Optimizers
- 6.5Module 5: Activation Functions
- 6.6Module 6: Building Artificial Neural Networks
- 6.7Module 7: Modern Deep Learning Optimizers and Regularization
- 6.8Module 8: Building Deep Neural Networks Using Keras
- 6.9Module 9: Convolutional Neural Networks (CNNs)
- 6.10Module 10: Word Embedding
- 6.11Module 11: Recurrent Neural Networks (RNNs)
- 6.12Module 12: Generative Adversarial Networks (GANs)
- 6.13Module 13: Speech Recognition APIs
- 6.14Module 1 Introduction to Artificial Neural Networks (Assignment Questions)1 Week
- 6.15Module 2 Introduction to Deep Learning (Assignment Questions)1 Week
- 6.16Module 3 TensorFlow Basics (Assignment Questions)1 Week
- 6.17Module 4 Optimizers (Assignment Questions)1 Week
- 6.18Module 5 Activation Functions (Assignment Questions)1 Week
- 6.19Module 6 Building Artificial Neural Networks (Assignment Questions)1 Week
- 6.20Module 7 Modern Deep Learning Optimizers and Regularization (Assignment Questions)1 Week
- 6.21Module 9 Convolutional Neural Networks (CNNs) (Assignment Questions)1 Week
- 6.22Module 10 Word Embedding (Assignment Questions)1 Week
- 6.23Module 11 Recurrent Neural Networks (RNNs) (Assignment Questions)1 Week
- 6.24Module 8 Building Deep Neural Networks Using Keras (Assignment Questions)1 Week
- 6.25Module 12 Generative Adversarial Networks (GANs) (Assignment Questions)1 Week
- 6.26Module 13 Speech Recognition APIs (Assignment Questions)1 Week
- 6.27Deep Learning & Neural Networks1 Hour50 Questions
- Capstone Project1
- ADVANCE EXCEL19
- 8.1Module 1: Excel Basics and Customization
- 8.2Module 2: Advanced Functions and Formulas
- 8.3Module 3: Data Validation Techniques
- 8.4Module 4: Data Organization and Analysis
- 8.5Module 5: Power Functions for Data Analytics
- 8.6Module 6: Data Visualization Techniques
- 8.7Module 7: Macros and Automation
- 8.8Module 8: What-If Analysis Tools
- 8.9Module 9: New Features and Enhancements in Excel
- 8.10Module 1 Excel Basics and Customization (Assignment Questions)1 Week
- 8.11Module 2 Advanced Functions and Formulas (Assignment Questions)1 Week
- 8.12Module 3 Data Validation Techniques (Assignment Questions)1 Week
- 8.13Module 4 Data Organization and Analysis (Assignment Questions)1 Week
- 8.14Module 5 Power Functions for Data Analytics (Assignment Questions)1 Week
- 8.15Module 6 Data Visualization Techniques (Assignment Questions)1 Week
- 8.16Module 7 Macros and Automation (Assignment questions)1 Week
- 8.17Module 8 What-If Analysis Tools (Assignment Questions)1 Week
- 8.18Module 9 New Features and Enhancements in Excel (Assignment Questions)1 Week
- 8.19ADVANCE EXCEL1 Week50 Questions
- VBA (Visual Basic for Applications)17
- 9.1Module 1: Introduction to VBA
- 9.2Module 2: Automating Data Tasks with Macros
- 9.3Module 3: Fundamental VBA Programming Concepts
- 9.4Module 4: Working with Excel Objects
- 9.5Module 5: Data Cleaning and Transformation
- 9.6Module 6: Advanced Data Manipulation Techniques
- 9.7Module 7: User-Defined Functions (UDFs) for Data Analysis
- 9.8Module 8: Data Visualization and Reporting
- 9.9Module 1 Introduction to VBA (Assignment Questions)1 Week
- 9.10Module 2 Automating Data Tasks with Macros (Assignment Questions)1 Day
- 9.11Module 3 Fundamental VBA Programming Concepts (Assignment Questions)1 Day
- 9.12Module 4 Working with Excel Objects (Assignment Questions)1 Day
- 9.13Module 5 Data Cleaning and Transformation (Assignment Questions)1 Week
- 9.14Module 6 Advanced Data Manipulation Techniques (Assignment Questions)1 Week
- 9.15Module 7 User-Defined Functions (UDFs) for Data Analysis (Assignment Questions)1 Week
- 9.16Module 8 Data Visualization and Reporting (Assignment Questions)1 Week
- 9.17VBA (Visual Basic for Applications)1 Hour50 Questions
- Tableau14
- 10.1Module 1: Tableau Overview
- 10.2Module 2: Data Sources
- 10.3Module 3: Worksheets
- 10.4Module 4: Calculations
- 10.5Module 5: Sorting & Filtering
- 10.6Module 6: Data Visualization
- 10.7Module 7: Projects
- 10.8Module 1 Tableau Overview (Assignment Questions)1 Week
- 10.9Module 2 Data Sources (Assignment Questions)1 Week
- 10.10Module 3 Worksheets (Assignment Questions)1 Week
- 10.11Module 4 Calculations (Assignment Questions)1 Week
- 10.12Module 5 Sorting & Filtering (Assignment Questions)1 Week
- 10.13Module 6 Data Visualization (Assignment Questions)1 Week
- 10.14Tableau1 Hour50 Questions
- Power BI11
- 11.1Module 1: Introduction to Power BI
- 11.2Module 2: Data Visualization
- 11.3Module 3: Power BI Service, Publishing & Sharing
- 11.4Module 4: Data Transformation
- 11.5Module 5: Data Modeling & DAX
- 11.6Module 1 Introduction to Power BI (Assignment Questions)1 Week
- 11.7Module 2 Data Visualization (Assignment Questions)1 Week
- 11.8Module 3 Power BI Service, Publishing & Sharing (Assignment Questions)1 Week
- 11.9Module 4 Data Transformation (Assignment Questions)1 Day
- 11.10Module 5 Data Modeling & DAX (Assignment Questions)1 Week
- 11.11Power BI1 Hour50 Questions
- Final Exam2
CodeCodence Instructor

1 Student12 Courses
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₹120,000.00₹34,999.00
100% positive reviews
205 students
92 lessons
Language: Hindi
11 quizzes
Assessments: Yes
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