100-Day Data Science & AI Career Accelerator

What you will learn:

Master Python programming, statistics, and data manipulation for data science.
Perform data cleaning, feature engineering, and exploratory data analysis (EDA).
Build and evaluate various machine learning models for regression, classification, and clustering.
Implement deep learning models using TensorFlow/Keras for image and text processing.
Explore Generative AI and Large Language Models (LLMs), practicing prompt engineering.
Solve industry case studies including customer churn prediction and sales forecasting.
Develop an end-to-end data science project from data acquisition to insightful dashboards.
Build a compelling portfolio and resume to launch your Data Science/AI career.

Description

Launch your data science and AI career with our intensive 100-day program. This comprehensive course equips you with in-demand skills, real-world projects, and a portfolio to land your dream job. Learn Python programming, data analysis, machine learning, deep learning, and generative AI techniques through a structured curriculum.

You'll tackle practical case studies, including customer churn prediction, sales forecasting, and building recommendation systems. Build a robust portfolio through hands-on labs and a challenging capstone project that showcases your end-to-end data pipeline development skills. We'll even guide you in crafting a compelling resume and personal brand to maximize your career prospects. This isn't just theory; it's about transforming your knowledge into actionable results and landing your ideal role in the exciting world of Data Science and AI.

What you'll gain:

100 days of structured learning and practical application
Multiple portfolio-ready projects to showcase your skills
Mastery of Python, data analysis, machine learning, deep learning, and generative AI
Hands-on experience with real-world datasets and industry case studies
A polished portfolio and resume tailored to Data Science and AI roles
Confidence and the skills to launch a successful career in Data Science and AI

Don't just learn—transform your career. Enroll now and start your journey to Data Science and AI mastery!

Curriculum

Phase 1: Data Science Foundations (Days 1-20)

This foundational phase introduces the core concepts of data science. Begin by mastering Python programming fundamentals, including variables, loops, functions, and object-oriented programming (OOP). You will then delve into essential data handling techniques with NumPy and Pandas libraries. Learn to create effective data visualizations with Matplotlib and Seaborn. Finally, you will solidify your understanding of statistical concepts, including mean, variance, distributions, and hypothesis testing. The phase concludes with a hands-on lab to apply what you've learned.

Phase 2: Data Wrangling & Exploration (Days 21-35)

This phase focuses on preparing data for analysis. You'll master data cleaning techniques, addressing missing values, duplicates, and outliers. Learn how to perform feature engineering, including encoding, scaling, and transformations. You'll then delve into the crucial skill of exploratory data analysis (EDA), interpreting insights from real-world case studies. This section also includes a hands-on lab allowing you to put your newly acquired skills into practice.

Phase 3: Core Machine Learning (Days 36-55)

Dive into the world of machine learning algorithms. You will learn the fundamentals of machine learning, the train-test split method and different evaluation metrics. You will build and evaluate regression models (Linear, Logistic, Ridge, Lasso), and classification models (Decision Trees, Random Forest, SVM, KNN). You'll also explore unsupervised learning techniques like K-Means clustering and Principal Component Analysis (PCA), applying them to relevant use cases. This section also includes a hands-on lab.

Phase 4: Applied Machine Learning & Projects (Days 56-70)

Apply your machine learning knowledge through real-world case studies. You'll develop predictive models for customer churn prediction (classification), sales forecasting (time-series analysis), and build recommendation systems using collaborative filtering. Each case study will provide valuable hands-on experience and strengthen your problem-solving abilities. A hands-on lab is included for reinforced learning.

Phase 5: Deep Learning Fundamentals (Days 71-85)

Explore the exciting world of deep learning. You'll learn the fundamentals of neural networks, including perceptrons and forward/backpropagation. You will gain practical experience with TensorFlow/Keras, building deep learning models for image classification (CNNs) and text processing (RNNs/LSTMs). This section will equip you with the skills to tackle complex problems using deep learning techniques. A hands-on lab is included.

Phase 6: Generative AI & Advanced Applications (Days 86-95)

Delve into the latest advancements in AI with Generative AI. Explore Large Language Models (LLMs) such as GPT and BERT, understanding transformer architectures. Learn the art of prompt engineering and fine-tuning techniques. Understand the applications of AI in business (automation, NLP, chatbots) and various industries (aviation, healthcare, finance). You'll conclude this phase with another hands-on lab.

Phase 7: Capstone Project & Career Launch (Days 96-100)

Culminate your learning journey with a comprehensive capstone project. You'll design and implement an end-to-end data pipeline, including data acquisition, model building, dashboard creation, and extracting actionable business insights. You’ll also focus on creating a professional portfolio and resume tailored for Data Science and AI roles. The final day will involve a presentation of your capstone project and guidance on future learning paths (MLOps, advanced deep learning, specialization within a specific domain).

Deal Source: real.discount