Professional Certificate in Data Analytics
In this Opex-Analytica certificate program, you’ll learn how data analytics professional turn data into a competitive advantage for their organization in the specific areas of marketing, telecom, banking, human resources, finance, retail, healthcare, and operations, and you’ll develop basic data literacy and an analytic mindset that help you make strategic decisions. This includes:
• Transforming real-world datasets into actionable recommendations
• Mastering technical and strategic thinking skills and frameworks
• Developing an advanced ability to use visualization tools and other data skills
Plus, our online certificate program covers all relevant data analytics tools, including:
Excel, SQL, PowerBI, Python, Pandas, Numpy, Matplotlib, Seaborn, Scikit-Learn
What you learn in the Professional Data Analytics Certification Program?
Training Modules Overview
Fundamentals of Statistics
Python Foundation
Python Foundation
- Anaconda and Python IDE – Jupyter Lab
- Python programming – Basics
Introduction to Statistics – The Basics
Introduction to Statistics – The Basics
- Introduction to Statistics
- Measures of central tendency (Mean, Mode, Median)
- Measures of dispersion (Range, Standard Deviation)
- Basics of Probability, Distributions
- Random Variables (Discrete and Continuous)
- Conditional Probability (Bayes Theorem)
Introduction to Statistics – The Basics
A) Data Analytics:
• What is this?
• How is it used?
• What are its 4 basic techniques?
B) Introduction to Python
• Anaconda and Python IDE – Jupyter Lab
• Python Programming – Basics
C) Mathematics and Statistics – The fundamentals
• Introduction to Univariate Descriptive Statistics
• Measure of Central Tendency (Mean, Mode, Median)
• Measure of Dispersion (Variance, Standard Deviation, Range/IQR)
• Probability Distribution
• Random variables (discrete and continuous)
• Conditional probability (Bayes’ theorem)
D) Bivariate Descriptive Statistics
• Graphical representation of two variables
• Regression and Correlation
Data Analytics and Visualization in EXCEL
Manipulating Data in Excel
Manipulating Data in Excel
- Data Cleaning Techniques in Excel
- Logical functions: IF, AND, OR, IFERROR
- Date and Time functions
- Text functions: TEXT, SEARCH, LEN, LEFT, MID, RIGHT
- Use and application of VLOOKUP, HLOOKUP functions and their limitations
- Using INDEX, MATCH, OFFSET
- Conditional formatting
- Data Aggregation and Summarization using Pivot Tables
Visualization & Reporting Dashboard
Visualization & Reporting Dashboard
- Overview of chart types – column/bar charts, line/area, pie, doughnut charts, scatter plots
- How to select right chart for your data
- Creating and customizing advance charts
- Pivot Table Analysis & Charts
- Dashboard Structure Design
- Creating the charts and visuals
- Making the Dashboard Dynamic
- Customizing the visuals and putting it all together
Relational Database Concepts
Data Management (RDBMS – SQL)
Data Management (RDBMS – SQL)
- Introduction to RDBMS
- Data Storage
- Database Querying in SQL
- Joining Tables of Data
- Performing Subqueries
Exploratory Data Analysis (EDA) and Modelling using Python
Data Manipulation and Visualization (Pandas, Matplotlib & Seaborn)
Data Manipulation and Visualization (Pandas, Matplotlib & Seaborn)
- Data Wrangling & Sub-setting
- Combining & Exporting Data
- Grouping & Aggregating Data
- Data Visualization
Predictive Modelling using Python
Predictive Analytics using Classification and Regression Models
Predictive Analytics using Classification and Regression Models
- Introduction to Predictive Analytics
- Supervised Machine Learning: Regression and Classification – Understanding the drivers
- Unsupervised Machine Learning: Clustering and Dimensionality Reduction (PCA) – Discovering similarities
Text Analytics & Natural Language Processing (NLP)
Text Analytics & Natural Language Processing (NLP)
- Introduction to NLP and Python
- Hands-on session through the implementation of techniques such as: tokenization implementation using Python programming. Understand stemming, lemmatization, and stopwords
- Applications: Sentiment Analysis, Text Classification
What you need:
1
The motivation to transform your career: This is a rigorous certificate program that requires some commitment as it takes a minimum of 15-20 hours per week to complete in 3 months (14 week-ends).
2
A written and spoken French skills and a basic knowledge of English language
3
A computer (Windows, macOS, or Linux) with a webcam, microphone, and a minimum of 10Go of free disk space
4
A reliable internet connection
Who is this course for?
This course is suitable for anyone who wants to start a career in data analysis or for those who want to enhance their existing skills in this field.
No prior knowledge of data analysis is required to enroll in this professional certificate training program. However, learners are expected to possess basic mathematics and statistics skills, which will help them warm-up their basic math and statistical skills. An interest in mathematical and logical thinking
No prior experience of Python is assumed, although prior experience will be an advantage
- Benefits
- Learn the latest in your chosen industry or subject
- Complete the training program and earn a professional certification
- Impress employers with learning outcomes you can add to your CV
- Make your career dreams a reality
- Career path
- Data Analyst
- Data Scientist
- Data Analytics Consultant
- Marketing Data Analyst
- Retail Data Analyst
- Data Quality Analyst
- Risk Analyst