Diploma in Data Science and Data Analytics with Python for Data Analyst
2 Courses Bundle | CPD Accredited | Free Ebook | Lifetime Access | Easy Refund
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Summary
- Accredited Certificate on Data Analysis Course From Learndrive - Free
- Exam(s) / assessment(s) is included in price
- Tutor is available to students
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Overview
Diploma in Data Science and Data Analytics with Python for Data Analyst
Embark on a transformative journey with our Diploma in Data Science and Data Analytics using Python, meticulously designed for aspiring data analysts. This program lays the foundation with Python programming essentials before advancing to complex Data Analysis and Data Science concepts.
Key Performance Metrics:
- Master Python fundamentals for Data Analysis and Data Science projects.
- Proficiency in manipulating Python data types and structures for Data Analysis challenges.
- Develop robust Python applications with effective error handling for Data Analysis tasks.
- Harness NumPy for numerical manipulation and Pandas for data analysis in Data Science.
- Utilise Matplotlib and Python visualization tools for clear data communication.
- Explore machine learning basics within the Python ecosystem for predictive analysis.
- Apply Python skills to practical Data Science scenarios for model building and validation.
- Conduct thorough Exploratory Data Analysis to uncover patterns in data for Data Science.
- Enhance critical thinking skills for methodical problem-solving in Data Science with Python.
Courses Included:
- Course 1: Diploma in Python Fundamentals
- Course 2: Data Science and Data Analytics
Accreditation:
This Data Analysis Diploma is CPDQE accredited, which serves as an impactful mechanism for skill enhancement.
Certificates
Accredited Certificate on Data Analysis Course From Learndrive
Digital certificate - Included
Course media
Resources
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Description
Key Lesson Snippets:
Course 1: Python Fundamentals
- Introduction to Python: Basics of Python programming, setting the foundation for Data Analysis and Data Science.
- Working with Data Types: Understanding Python data types essential for Data Science applications.
- Python Strings & List: Manipulating text and list data structures, crucial for data manipulation in Data Analysis.
- Python Casting and Input: Techniques for converting data types and handling user input, applicable in Data Analytics.
- Python Dictionary: Utilizing key-value pairs for efficient data storage and retrieval in Data Science projects.
- Python Date and Time: Handling temporal data, a common requirement in Data Analysis tasks.
- Creating a Function: Modularizing code for reusability and simplicity in Data Analysis algorithms.
- Error Handling: Ensuring robust Data Analysis applications through effective error management.
- Python File Handling: Reading from and writing to files, a key skill for data processing in Data Science.
- Python Modules: Utilizing and creating modules to extend Python's capabilities for Data Analysis.
Course 2: Data Science and Data Analytics
- Introduction to Data Science: Overview of Data Science, understanding its significance in analysing data.
- Data Science Environment Setup: Configuring the development environment for Data Science and Data Analysis projects.
- Working with the NumPy Package: Performing numerical computations fundamental to Data Analysis.
- Working with Pandas Data Science Package: Data manipulation and analysis using Pandas, a cornerstone in Data Science.
- Data Preprocessing: Techniques for cleaning and preparing data for analysis, a vital step in the Data Science process.
- Exploratory Data Analysis (EDA): Analysing datasets to summarize their main characteristics, often using visualization.
- Building Predictive Models: Using Python to create models that predict future trends based on data.
- Data Visualisation Techniques: Advanced methods for presenting data findings effectively in Data Science projects.
Career path
- Data analyst
- Data Scientist
- Data Analytics Consultant
- Data science intern
- Python Data Scientist
- Python Developer
- Python Data Analyst
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This course is advertised on Reed.co.uk by the Course Provider, whose terms and conditions apply. Purchases are made directly from the Course Provider, and as such, content and materials are supplied by the Course Provider directly. Reed is acting as agent and not reseller in relation to this course. Reed's only responsibility is to facilitate your payment for the course. It is your responsibility to review and agree to the Course Provider's terms and conditions and satisfy yourself as to the suitability of the course you intend to purchase. Reed will not have any responsibility for the content of the course and/or associated materials.
