Data Science with Python
A Data Science with Python course typically covers Python programming basics, data analysis techniques, data visualization, and machine learning concepts. It may also include topics like data wrangling, feature engineering, and statistical analysis using Python libraries like Pandas, NumPy, and Scikit-learn.
A “Data Science with Python” course typically covers foundational Python programming, data manipulation using libraries like Pandas and NumPy, data visualization with Matplotlib and Seaborn, and machine learning with scikit-learn. It often includes statistical concepts like hypothesis testing, and explores topics like data cleaning, exploratory data analysis (EDA), and model evaluation. The course might also delve into big data, data engineering, and ethical considerations in data science.
Python Programming Fundamentals: This includes data types, operators, control structures, functions, classes, and object-oriented programming concepts.
Data Structures: Understanding lists, tuples, dictionaries, and sets in Python.
Data Manipulation and Wrangling: Learning how to load, clean, and transform data using Pandas.
Data Analysis: Exploratory data analysis (EDA), data cleaning, and handling missing values.
Data Visualization: Using libraries like Matplotlib and Seaborn to create visualizations.
Statistics and Probability: Concepts like descriptive statistics, distributions, sampling, and hypothesis testing.
Machine Learning: Introduction to various machine learning algorithms, including linear and logistic regression, clustering, and classification.
Model Building and Evaluation: Learning how to train, evaluate, and refine machine learning models.
Data Preprocessing: Techniques like scaling, normalization, and handling categorical data.
Advanced Topics: Depending on the course, it might delve into topics like web scraping, APIs, and big data analysis using Spark.
What is data science?
Data Science. It is the discipline that allows a company to explore and analyze the raw data of the transformers into valuable information that helps solve business problems. The idea is to create methods of recording, storing and analyzing data to allow its exploitation as a source of information, as science for the company.
How to become a data engineer?
The data engineer must have a high level of expertise enabling him to successfully carry out his mission of developing data flows. He is a specialist in structured languages such as Javascript, Scala and Python. He also has skills in the design of databases that he creates using SQL and NoSQL. The production of the Data Engineer must be readable and easy to manipulate afterwards.
Who are the data courses for?
Whether it is for people with a basic knowledge of mathematics, statistics or computer science who are looking to retrain or for developers wishing to increase their skills in Data Sciences, our courses are adapted to many profiles. Moreover, our “à la carte” offer will allow Data specialists already in place to increase their skills on certain notions.
Kerala
Thiruvalla, Pandalam, Adoor, Pathanamthitta, Kayamkulam, Kottayam, Marthandam, Neyyattinkkara, Nedumangad, Thiruvananthapuram City, Kilimanoor, Karikode, Kollam City, Karunagapally, Punalur, Anchal, Kuttikkanam, Elappara, Kalamassery, Kaloor, Angamali, Thrissur, Palakkad, Manjeri, Valanchery, Perinthalmanna, Calicut (Kozhikode), Perumbavoor, Vyttilla, Alappuzha, Harippad.
Tamil Nadu
Velachery, Anna Nagar, Thiruvattiyoor, Neyveli, Aranthangi, Pudukottai, Nagapattinam, Karaikal, Ariyalur, Mulumichampatti, Saravanampatti, Gandhipuram, Kumbakonam, Mayiladuthurai, Vaniyambadi, Vellore, Tirupattur (Vellore), Kancheepuram, Thiruvannamalai, Hosur, Hosur East.
Karnataka
Bangalore Electronic City, Mysore Kuvempunagar, Mysore City.
Andhra Pradesh
Panruti, Dilsukhnagar, Chittoor, West Godavari.
Maharashtra
Panvel, Dombivli, Dombivli East, Thane, Kalyan, Akurdi, Chinchwad, Nigdi, Karvenagar, Revet, Kothrud.
West Bengal
Kolkata, Durgapur.
Rajasthan
Sikar, Kota, Jhalawar.
Jharkhand
Ranchi.
Uttar Pradesh
Allahabad, Lucknow, Rambagh.