Explore the dynamic field of data analytics with Python with our intensive course. This online Diploma in Data Analytics With Python Course is designed to offer a comprehensive insight into all aspects of the data analytics process, providing a solid foundation for any individual wishing to pursue a career in data analytics across a range of diverse industries. Dive into hands-on exercises and real-world projects as you harness the power of Python libraries such as Pandas, NumPy, and Matplotlib to analyze and visualize data effectively. Whether you're a beginner or an experienced analyst, this course will equip you with the knowledge, skills and confidence to uncover valuable insights, make data-driven decisions, and propel your career in the rapidly evolving field of data analytics.
In today's world, data is everywhere. From the websites you visit to the purchases you make, businesses, governments, and organizations collect massive amounts of information. But what does all this data mean? How can we make sense of it all? That's where data analytics comes in. Data analytics is the process of systematically examining data to uncover patterns, trends, and insights that can inform decisions and drive progress. It's a powerful tool that can be used to improve business strategies, optimise processes, enhance product development and make evidence based decisions.
This Data Analytics Using Python Programme is 11 weeks duration and a valuable investment in your professional development, leading to increased job opportunities, career advancement, CV-enhancing qualifications, and improved earning potential. - Download The Professional Courses Brochure
Week 1: Introduction to Data Analysis
Week 2: Data Preparation
Week 3: Descriptive Statistics
Week 4: Data Visualization
Week 5: Exploratory Data Analysis (EDA)
Week 6: Introduction to Hypothesis Testing
Week 7: Advanced Analysis Techniques I
Week 8: Regression Analysis
Week 9: Introduction to Classification
Week 10: Advanced Analysis Techniques II
Week 11: Communicating Results & Next Steps
Materials provided: All photocopies/handouts and PowerPoint presentations provided
Delivery: Live Online Classes
Data Understanding:
Distinguish between different types of data (quantitative, qualitative, structured, unstructured).
Identify sources of data relevant to specific problems.
Evaluate data quality and identify potential biases.
Data Preparation:
Clean and transform data using common techniques (e.g., handling missing values, outliers).
Format and structure data for analysis.
Exploratory Analysis:
Calculate descriptive statistics (e.g., measures of central tendency and spread).
Create visualizations (e.g., histograms, scatterplots, box plots) to explore data distributions and relationships.
Hypothesis Testing:
Formulate testable hypotheses.
Conduct basic statistical tests (e.g., t-tests, correlation analysis).
Interpret the results of hypothesis tests.
Communication:
Select appropriate visualizations for different data types and insights.
Explain data analysis results clearly to non-technical audiences.
Create concise and informative data analysis reports.
Upon completion of the Data Analytics Course, you will receive:
This data analysis course aims to equip students with the fundamental knowledge and skills to understand the complete data analysis process, from problem formulation to data collection, cleaning, analysis, visualization, and interpretation.
Students will develop critical thinking and problem-solving skills needed to apply data-driven approaches to address real-world issues across various fields.
The course also emphasizes the ability to effectively communicate insights, enabling students to clearly present and explain findings to both technical and non-technical audiences through visualizations and reports.
By the end of this course, students will be able to identify different data types and select appropriate analysis techniques, clean and prepare raw datasets, perform exploratory data analysis using descriptive statistics, create compelling visualizations, conduct basic hypothesis testing, use data analysis software proficiently, and apply these concepts to real world data.
Data Analysis with python
Taking a data science with Python course opens a wide range of exciting opportunities. Upon completion could transition to roles as a data analyst, delving into data to find patterns that guide business decisions. Or perhaps a business analyst, bridging the gap between data and business insights.
If you enjoy the challenge of prediction and complex datasets, a career as a data scientist might be the path for you.
Machine learning engineers focus on the practical application of models. Beyond these specific roles, data science with Python courses will equip you with in-demand skills like problem-solving, programming, statistical analysis, and data communication. The possibilities extend to various industries like finance, marketing, and healthcare.
To secure a place on this course a non-refundable deposit of €150 applies. A discount of 10% applies to this course if deposit paid before 1 June 2024.
Course Fee: €990.00 - Pay deposit before 1st June and get a 10% Discount = Fee: €890.00
Deposit €150.00 Secures your place on the course
| 1st Instalment: 01/10/24 | €370.00 |
| 2nd Instalment: 12/11/24 | €370.00 |
