Data Science Course Overview
Master Data Science and Launch a High-Paying CareerBecome a skilled Data Scientist with our comprehensive Data Science Certification Course designed for beginners, graduates, working professionals, and career changers. Learn the most in-demand data science tools, techniques, and technologies used by leading companies worldwide.This industry-focused program covers Python Programming, Statistics, Machine Learning, Deep Learning, Data Visualization, Artificial Intelligence, SQL, Big Data, and Generative AI through hands-on projects and real-world case studies.
What You Will Learn
By completing this Data Science course, you will develop the
practical skills required to work with data and build machine
learning solutions.
Python programming for Data Science
Statistics and probability fundamentals
NumPy for numerical computing
Pandas for data manipulation and analysis
Data cleaning and preprocessing
Exploratory Data Analysis (EDA)
Data visualisation with Matplotlib and Seaborn
SQL and database querying
Supervised Machine Learning
Unsupervised Machine Learning
Feature engineering and model selection
Model evaluation and optimisation
Data Science Course Syllabus
10 Modules
80 Hours Total
12 Projects
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Introduction to Python and Data Science
1 hr
-
Variables, data types, operators and expressions
1 hr
-
Conditional statements and loops
1 hr
-
Functions, modules and packages
1.5 hrs
-
Lists, tuples, dictionaries and sets
1.5 hrs
-
Project: Python Data Processing Application
2 hrs
-
Descriptive statistics and measures of central tendency
1 hr
-
Mean, median, mode, variance and standard deviation
1 hr
-
Probability fundamentals
1 hr
-
Distributions and normal distribution
1.5 hrs
-
Correlation and covariance
1 hr
-
Project: Statistical Analysis of Business Dataset
1.5 hrs
-
NumPy arrays and numerical operations
1.5 hrs
-
Array indexing, slicing and broadcasting
1 hr
-
Pandas Series and DataFrames
1.5 hrs
-
Data filtering, sorting and grouping
1 hr
-
Merging, joining and reshaping datasets
1.5 hrs
-
Project: Customer Data Analysis using Pandas
1.5 hrs
-
Understanding real-world datasets
1 hr
-
Handling missing and duplicate values
1.5 hrs
-
Data type conversion and preprocessing
1 hr
-
Outlier detection and treatment
1.5 hrs
-
Exploratory Data Analysis techniques
1.5 hrs
-
Project: End-to-End EDA on Business Dataset
1.5 hrs
-
Introduction to data visualisation
1 hr
-
Matplotlib fundamentals
1.5 hrs
-
Seaborn charts and statistical visualisation
1.5 hrs
-
Choosing the right chart for business data
1 hr
-
Project: Interactive Business Insights Dashboard
2 hrs
-
Database concepts and relational databases
1 hr
-
SELECT, WHERE, ORDER BY and filtering
1 hr
-
GROUP BY, HAVING and aggregate functions
1.5 hrs
-
JOINs, subqueries and advanced SQL
2 hrs
-
Project: Business Data Analysis using SQL
1.5 hrs
-
Introduction to Machine Learning
1 hr
-
Machine Learning workflow and lifecycle
1 hr
-
Supervised vs Unsupervised Learning
1.5 hrs
-
Train-test split and cross-validation
1.5 hrs
-
Feature engineering and preprocessing
2 hrs
-
Project: Predictive Machine Learning Model
2 hrs
-
Linear Regression and Multiple Regression
1.5 hrs
-
Logistic Regression
1.5 hrs
-
Decision Trees and Random Forest
2 hrs
-
K-Nearest Neighbours and Support Vector Machines
2 hrs
-
Model evaluation metrics
1.5 hrs
-
Project: Customer Churn Prediction
1.5 hrs
-
Clustering concepts and applications
1 hr
-
K-Means clustering
1.5 hrs
-
Hierarchical clustering
1.5 hrs
-
Dimensionality reduction with PCA
2 hrs
-
Project: Customer Segmentation System
2 hrs
-
End-to-end Data Science project planning
1 hr
-
Data collection, cleaning and EDA
2 hrs
-
Machine Learning model development
2 hrs
-
Model evaluation and presentation
1.5 hrs
-
GitHub portfolio, interview preparation and mock interviews
1.5 hrs
Who Should Attend
This Data Science training is suitable for learners who want to
build careers in data analytics, machine learning and artificial
intelligence.
Freshers & Students
BE/B.Tech, MCA, BCA, B.Sc and other graduates looking to
start a career in Data Science.
Career Switchers
Professionals from non-data backgrounds looking to transition
into data science and analytics roles.
Data Analysts
Existing analysts who want to strengthen their Python,
statistics and machine learning skills.
AI & ML Enthusiasts
Learners interested in predictive analytics, machine learning
and artificial intelligence.
Tools & Technologies Covered
Get practical experience with popular tools and technologies used
throughout the modern Data Science workflow.
Data Science Certification Path
Complete the training, practical assignments and capstone project
to receive your procode Technologies Data Science certificate and prepare
for recognised industry certification pathways.
procode Technologies Data Science Certificate
Awarded after successful completion of the course,
assessments and capstone project.
Microsoft Certified: Power BI Data Analyst
Career pathway for learners interested in business intelligence,
reporting and data visualisation.
AWS Certified Machine Learning Engineer
Advanced pathway for professionals interested in machine
learning workloads on AWS.
Data Science & Machine Learning Career Path
Continue into advanced machine learning, deep learning,
MLOps and artificial intelligence specialisations.
