.jpg "5 Udemy Paid Courses for Free with Certification. (Limited Time for Enrollment)")
5 Udemy Paid Courses for Free with Certification. (Limited Time
for Enrollment)
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1. How to Become a Successful Software Programming Developer
One of unique computer software development courses that can help you engineer game plan for a great software career
What you'll learn
- What all to do to become a successful Software Developer-Overview
- What to learn and practice to become a software developer
- How to prepare for software developer interviews
- How to apply for software development internships and jobs
- How to explore career growth in software development
2. HTML 5 With Quizzes And Python 3 Complete Course
Python 3: Learn HTML5 with Quizzes, Explore Python Basics and Advanced Concepts in a Comprehensive Python Course
What you'll learn
- HTML 5 Introduction, Use of Tags, Forms, Tables In HTML 5,
- Go from Beginner to Advanced in Python Programming by learning all the basics to object-oriented programming.
- Write scripts for general productivity tasks Read and comprehend Python code Gain knowledge with general programming concepts
- Use variables to store, retrieve, and calculate information
- Utilize core programming tools such as functions and loops
3. Complete Python and Machine Learning in Financial Analysis
Using Python, Machine Learning, and Deep Learning in Financial Analysis with step-by-step coding (with all codes)
What you'll learn
- You will be able to use the functions provided to download financial data from a number of sources and preprocess it for further analysis
- You will be able to draw some insights into patterns emerging from a selection of the most commonly used metrics (such as MACD and RSI)
- Introduces the basics of time series modeling. Then, we look at exponential smoothing methods and ARIMA class models.
- shows you how to estimate various factor models in Python. one,three-, four-, and five-factor models.
- Introduces you to volatility forecasting using (G)ARCH class models, how to choose the best-fitting model, and how to interpret your results.
- Introduces the the concept of Monte Carlo simulations and uses them to simulate stock prices, evaluate European/American options, and calculate the VaR.
- Introduces the Modern Portfolio Theory and shows you how to obtain the Efficient Frontier in Python. how to evaluate the performance of such portfolios.
- Presents a case of using machine learning for predicting credit default. You will get to know and tune the hyperparameters of the models and handle imbalances
- Introduces you to a selection of advanced classifiers (including stacking multiple models)and how to deal with class imbalance, using Bayesian optimization.
- Demonstrates how to use deep learning techniques for working with time series and tabular data. The networks will be trained using PyTorch.
4. Data Visualization with Python and New Methods in Matplotlib
Step-by-step training for 3D and advanced visualization in Python and Matplotlib (with all the codes)
What you'll learn
- Designing and illustrating figures and plots in 3D
- Familiarity with Python libraries for data visualization
- Knowledge of new and practical diagrams to visualize data in different fields
- Create functions needed to draw plots professionally
- Familiarity with creating, collecting, and preparing data for visualization
5. Machine Learning and Deep Learning Projects in Python
20 practical projects of Machine Learning and Deep Learning and their implementation in Python along with all the codes
What you'll learn
- Introducing the structure of Machine Learning and Deep Learning and their application in real problems
- Introducing Machine Learning and Deep Learning algorithms and launching them in projects
- Implementing Machine Learning and Deep Learning algorithms in Python
- Familiarity with Python syntax for using Machine Learning and Deep Learning
- Familiarity with Prediction Models
- Data preparation and Visualization for use in Machine Learning and Deep Learning algorithms
- Using Case Studies in Projects
- Learning how to use APIs to collect up-to-date data and learn about different Data sets
- Introducing and using different Machine Learning and Deep Learning libraries in Python
- Getting to know different Neural Networks and using them in real projects
- Image processing using Artificial Neural Network (ANN) in Python
- Classification with Neural Networks using Python
- Familiarity with Natural Language Processing (NLP) and its use in projects
- Forecasting the amount of sales, product price, sales price, etc.
- Introducing and using algorithm validation metrics such as Confusion matrix, Accuracy score, Precision score, Recall score, F1 score, etc.
- +40 Cheat Sheets of Data Science, Machine Learning, Deep Learning and Python