Data Analytics – Self Paced

Unlock the power of data with our comprehensive Data Analytics course, designed as per the latest AICTE norms to help learners build a strong foundation in statistics, probability, machine learning, big data technologies, and advanced analytics tools. This program is ideal for professionals, students, and aspiring data scientists who want to transform raw data into actionable insights and drive business decisions.

The course begins with Statistics and Probability, covering hypothesis testing, ANOVA, regression analysis, Bayesian statistics, time series forecasting, and experimental design. You’ll master Python for Data Science, including NumPy, Pandas, Matplotlib, Seaborn, data cleaning, preprocessing, feature engineering, and text processing.

Advance into Machine Learning, where you’ll explore supervised, unsupervised, and semi-supervised learning, deep learning algorithms (CNNs, RNNs, LSTMs, Transformers), ensemble methods, and reinforcement learning. You’ll also learn Big Data Technologies like Hadoop, Spark, Hive, MongoDB, and stream processing for real-time analytics.

The program also focuses on Data Visualization & Exploration with tools like Tableau, Plotly, ggplot, Bokeh, and D3.js, along with geospatial and network visualization. In Natural Language Processing (NLP), you’ll work on sentiment analysis, topic modeling, NER, and advanced deep learning models for text.

Specialized modules include Time Series Analysis & Forecasting with ARIMA, SARIMA, Prophet, and deep learning methods for anomaly detection. Finally, you’ll gain hands-on skills in Deployment & Productionizing, learning Docker, Kubernetes, cloud platforms (AWS, Azure, Google Cloud), and building scalable ML pipelines.

By the end of this course, you’ll be industry-ready with job-oriented skills in Data Analytics, AI, and Big Data—equipped to solve real-world business challenges, secure high-paying roles, and accelerate your career growth.