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 internship 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 of the basics to Object Orientated Programming.
Write scripts for general productivity tasks Read and comprehend Python code Gain knowledge in regard to 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 the concept of volatility forecasting using (G)ARCH class models, how to choose the best-fitting model, and how to interpret your results.
Introduces concept of Monte Carlo simulations and use them for simulating stock prices, the valuation of European/American options and calculating 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 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, use 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

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