Which platform is used to perform coding operation?

The course utilizes Google Colab and MS SQL Server as the primary platform for coding operations. Learners may also use integrated development environments (IDEs) like Jupyter Notebook, PyCharm, Spyder, or VS Code for more extensive coding projects if desired.

Which softwares are needed before starting this course?

Install MS SQL Server and required Python libraries with corresponding IDE's such as PyCharm, Spyder, VS Code etc.

Do I need prior programming or database experience?

No prior experience is required; the course starts with fundamentals and builds up step by step.

Can I use these skills in my job or further study?

Yes, the skills are practical for entry-level analytics roles and form a foundation for advanced study in data science.

What will I get if I subscribe to this Specialization?

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Applied Data Analytics with Python and SQL

Q: Who Should Take This Course?

This course is designed for:Freshers looking to enter the fields of data analysis, data science, or artificial intelligence.Individuals with a keen interest in programming who want to enhance their technical skills.Professionals seeking to upskill in Python and data manipulation with SQL for practical applications in their careers.Anyone curious about data and eager to learn how to analyze and visualize it effectively. Whether you're starting your tech journey or looking to build a strong foundation, this course will guide you through the essentials of Python and SQL.

Dieser Kurs ist Teil von Spezialisierung „Applied Data Analytics“

Dozent: Edureka

1.680 bereits angemeldet

Bei enthalten

Mehr erfahren

4 Module

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

Stufe Mittel

Empfohlene Erfahrung

1 Woche zu vervollständigen

unter 10 Stunden pro Woche

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

4 Module

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

Stufe Mittel

Empfohlene Erfahrung

1 Woche zu vervollständigen

unter 10 Stunden pro Woche

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

Was Sie lernen werden

Write Python programs using core concepts like variables, data types, and control flow.
Implement NumPy and Pandas to analyze and process large datasets efficiently and accurately.
Create insightful data visualizations with Matplotlib, Seaborn, and Plotly for effective reporting.
Execute SQL queries to retrieve, manage, and analyze data from relational databases accurately.

Kompetenzen, die Sie erwerben

Kategorie: Data Visualization
Kategorie: Data Manipulation
Kategorie: Web Scraping
Kategorie: Data Structures
Kategorie: Data Visualization Software
Kategorie: Data Processing
Kategorie: Databases
Kategorie: Data Cleansing
Kategorie: SQL
Kategorie: Data Analysis
Kategorie: Data Wrangling

Werkzeuge, die Sie lernen werden

Kategorie: Jupyter
Kategorie: NumPy
Kategorie: Python Programming
Kategorie: Pandas (Python Package)

Wichtige Details

Zertifikat zur Vorlage

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15 Aufgaben

Unterrichtet in Englisch

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Dieser Kurs ist Teil der Spezialisierung Spezialisierung „Applied Data Analytics“

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Erwerben Sie ein Berufszertifikat zur Vorlage

In diesem Kurs gibt es 4 Module

Learn how to work with data using Python and SQL in a practical, project-based course designed to give you relevant, industry-ready skills. You’ll gain hands-on experience manipulating, querying, and analyzing large datasets preparing you to solve real-world data challenges in business, science, or technology.

By the end of this course, you’ll know how to: - Process and analyze data efficiently using Python, with a focus on Pandas and NumPy for manipulation and cleaning. - Write SQL queries to retrieve, filter, and aggregate data in relational databases. - Handle data files (CSV, Excel, JSON) and automate common data tasks for faster, repeatable analysis. - Visualize and report insights from your data to support decision-making. This course is designed for beginners, data enthusiasts, and aspiring data analysts and scientists. No prior programming experience is required, but some familiarity with databases or basic computing concepts will help you progress. You’ll finish with solid skills in Python scripting, SQL, and data analysis, giving you a strong foundation for further study or entry-level roles in data-driven industries.

This module is designed to help learners take a significant step towards launching their careers in data analytics. In the first week, we'll explore how Python programming concepts that are essential for creating efficient programs. Additionally, we'll delve into the role of pre-defined Python features in data analysis. Let's get started!

Das ist alles enthalten

38 Videos8 Lektüren5 Aufgaben3 Diskussionsthemen

38 Videos Insgesamt 190 Minuten

Course Introduction 6 Minuten
Programming Languages and Myths 7 Minuten
Python for AI/ML - Code Simplicity 4 Minuten
Python for AI/ML - Ease of Learning 5 Minuten
Identifiers in Python 5 Minuten
Literals in Python 7 Minuten
Arithmetic, Comparison, Logical, and Assignment Operators 6 Minuten
Bitwise, and Membership Operators 6 Minuten
Python Token Types 5 Minuten
Boolean Operators in Conditional Statement 4 Minuten
AND, OR, NOT in Python 4 Minuten
Working with Dictionaries 4 Minuten
Manipulating Dictionary 5 Minuten
Tuples in Python 4 Minuten
Working with Strings in Python 5 Minuten
Managing Strings 4 Minuten
Operations on String 5 Minuten
Creating Lists 4 Minuten
Immutable and Mutable Data Types 5 Minuten
Operations Performed on Lists 6 Minuten
Sets 7 Minuten
Manipulating Sets 1 Minute
Exploring Python's Built-in Functions 5 Minuten
Conditional Statement - if condition 3 Minuten
Conditional Statement - if else condition 5 Minuten
Initializing For loop 7 Minuten
Break, Continue and Pass Statement 4 Minuten
Validating Prime Numbers 4 Minuten
Mastering the While Loop in Python 6 Minuten
Opening Files 5 Minuten
File Operations 6 Minuten
Global vs. Local Variables in Python 8 Minuten
Introduction to Lambda Functions in Python 7 Minuten
Built-in Modules 6 Minuten
Standard Modules 6 Minuten
Creating User Defined Functions 6 Minuten
Functions with Multiple Parameters 4 Minuten
Summary of Python Essentials 2 Minuten

8 Lektüren Insgesamt 80 Minuten

Welcome to Applied Data Analytics with Python and SQL 10 Minuten
Starting with Python 10 Minuten
An Introduction to Python Data Types 10 Minuten
Built-in Functions in Python 10 Minuten
Conditional Statements and For Loop in Python 10 Minuten
Control Flow with Python: break, continue, and pass Statements 10 Minuten
Lambda Functions in Python 10 Minuten
File Handling with Python 10 Minuten

5 Aufgaben Insgesamt 42 Minuten

Practice Quiz : Python Programming Basics 3 Minuten
Practice Quiz : Working with Data Types in Python 3 Minuten
Practice Quiz : Conditional and Control Flow Statements 3 Minuten
Practice Quiz : Handling Files and File Operations 3 Minuten
Knowledge Check: Python Essentials for Programming 30 Minuten

3 Diskussionsthemen Insgesamt 30 Minuten

Introduce Yourself 10 Minuten
Differences in Sets, Tuples and Dictionary 10 Minuten
Have You Worked on Other Programming Language apart for Python 10 Minuten

During week two of the course, Learners will be taught how to handle data with NumPy and Pandas in various formats while developing skills to represent data visually using different types of charts and graphics.

Das ist alles enthalten

19 Videos5 Lektüren4 Aufgaben

19 Videos Insgesamt 91 Minuten

Introduction to NumPy in Python 6 Minuten
Hands-On with NumPy 5 Minuten
Introduction to Pandas in Python 4 Minuten
Working with Pandas Series 5 Minuten
Understanding Pandas DataFrames 5 Minuten
Data Manipulation with Pandas 4 Minuten
Combining Datasets with Pandas 6 Minuten
Matplotlib Library 5 Minuten
Plotting Charts 5 Minuten
Plotting Histogram and Box Plot 3 Minuten
Plotting Multiple Charts 6 Minuten
Introduction to Seaborn - Scatter Plot 6 Minuten
Seaborn Basic Charts 6 Minuten
Seaborn - HeatMap Manipulation 2 Minuten
Seaborn : Flights Dataset 5 Minuten
Seaborn: Gaining Insights in Flight Data 5 Minuten
Visualizing Charts with Plotly 5 Minuten
Customizing different charts in Plotly 6 Minuten
Summary of Exploring with NumPy and Pandas 2 Minuten

5 Lektüren Insgesamt 60 Minuten

NumPy in Python 10 Minuten
Getting Started with Pandas 10 Minuten
Data Visualization Fundamentals 20 Minuten
Data Visualization with Matplotlib 10 Minuten
Visualization with Seaborn 10 Minuten

4 Aufgaben Insgesamt 39 Minuten

Practice Quiz : Working with NumPy 3 Minuten
Practice Quiz : Handling Data using Pandas 3 Minuten
Practice Quiz : Visualizing Data in Python 3 Minuten
Knowledge Check: NumPy, Pandas and Data Visualization Libraries 30 Minuten

In this module, learners will explore methods for gathering information from various sources on the internet. They will utilize different Python libraries to process and organize the data for thorough evaluation, as well as connect MS SQL Server with Python.

Das ist alles enthalten

33 Videos4 Lektüren5 Aufgaben

33 Videos Insgesamt 155 Minuten

What is Web Scraping? 6 Minuten
Web Scraping Process Flow 5 Minuten
Managing Data 6 Minuten
Beautiful Soup 5 Minuten
Demonstration of Beautiful Soup 5 Minuten
Demonstration of Scrapy 3 Minuten
What is SQL? 5 Minuten
Operation on Keys 5 Minuten
Normalization in Databases 4 Minuten
Types of Normalization 1 NF 3 Minuten
Types of Normalization 2 NF 2 Minuten
Types of Normalization 3 NF 5 Minuten
Types of Normalization 4 NF 2 Minuten
Types of Normalization 5 NF 4 Minuten
Installation of MS SQL Server 6 Minuten
DDL Commands 6 Minuten
DQL Commands 6 Minuten
DML Commands 7 Minuten
DCL Commands 5 Minuten
TCL Commands 7 Minuten
Setting Up SQL Server 4 Minuten
Managing Foreign Key 3 Minuten
Inserting Data 7 Minuten
Deleting Data 3 Minuten
Alter Command 5 Minuten
Setting up Transaction 4 Minuten
Connecting with Database 7 Minuten
Creating Table 7 Minuten
Inserting Data 7 Minuten
Selecting Data 1 Minute
Updating Records 4 Minuten
Deleting Records 4 Minuten
Summary of Web Scraping and SQL 1 Minute

4 Lektüren Insgesamt 40 Minuten

Web Scraping Best Practices 10 Minuten
Difference Between MS SQL Server and MySQL 10 Minuten
SQL Commands 10 Minuten
Python with Microsoft SQL Server 10 Minuten

5 Aufgaben Insgesamt 42 Minuten

Practice Quiz : Web Scraping with Python 3 Minuten
Practice Quiz : SQL and Normalization 3 Minuten
Practice Quiz : Operations on SQL 3 Minuten
Practice Quiz : Integrating SQL with Python 3 Minuten
Knowledge Check : SQL, Normalizations and Web Scraping with Python 30 Minuten

This module is designed to assess an individual on the various concepts and teachings covered in this course. Evaluate your knowledge with a comprehensive graded quiz on Python programming concepts, Data manipulation with NumPy and Pandas with Web-Scraping with Python

Das ist alles enthalten

1 Video1 Lektüre1 Aufgabe1 Diskussionsthema

Erwerben Sie ein Karrierezertifikat.

Fügen Sie dieses Zeugnis Ihrem LinkedIn-Profil, Lebenslauf oder CV hinzu. Teilen Sie sie in Social Media und in Ihrer Leistungsbeurteilung.

Dozent

Edureka

157 Kurse 147.337 Lernende

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Häufig gestellte Fragen

This course offers a thorough practical application of Python and SQL. Created for Python enthusiasts, it focuses on hands-on skills for manipulating and analyzing data, allowing students to address actual data problems.

Learners will delve into the basics of Python and utilize tools such as NumPy and Pandas for effective data management. They will additionally make use of visualization tools like Matplotlib, Seaborn, and Plotly to present their findings in an efficient manner. Moreover, the course includes instruction on utilizing SQL for data manipulation, empowering students with the skills needed to make informed decisions based on data.

At the conclusion of the course, you will be fully equipped to utilize these skills in different data analysis situations, establishing a solid groundwork for future studies in data analytics.

This course is designed for:

- Freshers looking to enter the fields of data analysis, data science, or artificial intelligence.

- Individuals with a keen interest in programming who want to enhance their technical skills.

- Professionals seeking to upskill in Python and data manipulation with SQL for practical applications in their careers.

- Anyone curious about data and eager to learn how to analyze and visualize it effectively.

Whether you're starting your tech journey or looking to build a strong foundation, this course will guide you through the essentials of Python and SQL.

You’ll primarily use Python for programming and SQL for data handling, along with visualization libraries and database tools.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.