Welcome to our Certification Program for Data Science using Python!
This course is designed to provide you with the necessary skills and knowledge to become proficient in the field of Data Science using the Python programming language. The program is spread over a period of three months, where you will be introduced to the fundamental concepts of Data Science and Python in the first month, followed by Data Analysis and Visualization in the second month, and finally, Machine Learning and Project-based learning in the third month.
The program is structured to cater to the needs of beginners as well as professionals who are looking to enhance their skill set in the field of Data Science. The course will start by introducing you to the basics of Python programming and its libraries such as NumPy, Pandas, Matplotlib, and Seaborn, which are essential tools for data manipulation, analysis, and visualization. You will then learn how to use these tools to perform exploratory data analysis, data cleaning, and data preprocessing.
The second month of the course focuses on Data Visualization techniques with Matplotlib and Seaborn, Exploratory Data Analysis (EDA) with Pandas, and Data Preprocessing for Machine Learning. You will learn how to create visually appealing and informative plots using Matplotlib and Seaborn, and how to perform EDA to gain insights into your data. You will also learn how to preprocess your data to make it ready for machine learning algorithms.
In the final month of the course, you will delve deeper into Machine Learning algorithms, including supervised and unsupervised learning techniques. You will learn how to implement Linear Regression, Logistic Regression, Decision Trees, Random Forest, and Support Vector Machines (SVM) for supervised learning, and K-Means Clustering, Hierarchical Clustering, and Principal Component Analysis (PCA) for unsupervised learning. The course will culminate in a project where you will apply all the concepts you have learned throughout the program.
By the end of this program, you will be equipped with the skills and knowledge to tackle real-world data science problems using Python programming language. So, get ready to dive into the exciting world of Data Science using Python!
In this course, you will learn:
By the end of the course, you will be able to perform data analysis and machine learning tasks using Python programming language. You will be equipped with the necessary skills and knowledge to solve real-world data science problems and present your findings in a clear and concise manner.
To take this course, you should have some prior programming experience, preferably in Python. You should also have a basic understanding of statistics and linear algebra. Familiarity with concepts such as mean, median, standard deviation, and linear equations would be helpful.
However, even if you do not have prior programming experience or knowledge of statistics and linear algebra, you can still take this course. We will cover the necessary concepts and provide you with the required knowledge to follow along with the course.
Additionally, you should have access to a computer with an internet connection, as well as the ability to install Python and the required libraries. We will provide instructions on how to do this during the course.
The Certification Program for Data Science using Python offers several benefits, including:
Overall, the Certification Program for Data Science using Python is an excellent opportunity to develop your skills and advance your career in data science.
Month 1 – Data Science Fundamentals and Python Basics
Week 1: Introduction to Data Science, Python and its Ecosystem
Week 2: Python Data Structures and Control Flow
Week 3: Python Functions and Modules
Week 4: NumPy and Pandas for Data Manipulation
Month 2 – Data Analysis and Visualization with Python
Week 1: Data Visualization with Matplotlib
Week 2: Advanced Visualization with Seaborn
Week 3: Exploratory Data Analysis (EDA) with Pandas
Week 4: Data Preprocessing for Machine Learning
Month 3 – Machine Learning and Project-based Learning
Week 1: Introduction to Machine Learning
Week 2: Supervised Learning Algorithms
Week 3: Unsupervised Learning Algorithms
Week 4: Project-Based Learning
Here are the key aspects of how the training will work:
By the end of the course, you will have a strong understanding of Data Science using Python and the ability to build and deploy your own applications.