Pickl AI

AUGUST 9, 2024

Summary: A comprehensive Big Data syllabus encompasses foundational concepts, essential technologies, data collection and storage methods, processing and analysis techniques, and visualisation strategies. Fundamentals of Big Data Understanding the fundamentals of Big Data is crucial for anyone entering this field.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Pickl AI

NOVEMBER 4, 2024

Statistics Understand descriptive statistics (mean, median, mode) and inferential statistics (hypothesis testing, confidence intervals). These concepts help you analyse and interpret data effectively. Here are three critical areas worth exploring: Machine Learning, Data Visualisation, and Big Data.

Data Science 52

Data Science Python Machine Learning Machine Learning 52

Pickl AI

NOVEMBER 28, 2024

Concepts such as probability distributions, hypothesis testing , and Bayesian inference enable ML engineers to interpret results, quantify uncertainty, and improve model predictions. These techniques span different types of learning and provide powerful tools to solve complex real-world problems.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

FEBRUARY 12, 2024

Here are some key areas often assessed: Programming Proficiency Candidates are often tested on their proficiency in languages such as Python, R, and SQL, with a focus on data manipulation, analysis, and visualization. Differentiate between supervised and unsupervised learning algorithms.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Pickl AI

FEBRUARY 22, 2024

MicroMasters Program in Statistics and Data Science MIT – edX 1 year 2 months (INR 1,11,739) This program integrates Data Science, Statistics, and Machine Learning basics. It emphasises probabilistic modeling and Statistical inference for analysing big data and extracting information.

Hypothesis Testing 52

Hypothesis Testing Data Science Data Analysis Data Analysis 52

Pickl AI

MAY 31, 2023

Explore Machine Learning with Python: Become familiar with prominent Python artificial intelligence libraries such as sci-kit-learn and TensorFlow. Begin by employing algorithms for supervised learning such as linear regression , logistic regression, decision trees, and support vector machines.

Data Science 52

Data Science Python Data Scientist Machine Learning 52

Pickl AI

SEPTEMBER 12, 2024

Association Rule Learning: A rule-based Machine Learning method to discover interesting relationships between variables in large databases. B Big Data : Large datasets characterised by high volume, velocity, variety, and veracity, requiring specialised techniques and technologies for analysis.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52